About Life360

Life360’s mission is to keep people close to the ones they love. Our category-leading mobile app, Tile tracking devices, and Pet GPS tracker empower members to protect the people, pets, and things they care about most with a range of services, including location sharing, safe driver reports, and crash detection with emergency dispatch. Life360 serves approximately 91.6 million monthly active users (MAU), as of September 30, 2025, across more than 180 countries.

Life360 delivers peace of mind and enhances everyday family life with seamless coordination for all the moments that matter, big and small. By continuing to innovate and deliver for our customers, we have become a household name and the must-have mobile-based membership for families (and those friends who are basically family).

Life360 has more than 500 (and growing!) remote-first employees. For more information, please visit life360.com.

Life360 is a Remote-First company, which means a remote work environment will be the primary experience for all employees. All positions, unless otherwise specified, can be performed remotely (within the US) regardless of any specified location above. 

We are AI Native 

We are building an AI native company where AI is an integral part of how we build and operate. AI tool usage during interviews varies by role. You may be asked to demonstrate proficiency with AI tools, discuss how you leverage AI, or complete interview exercises without AI assistance. Your Recruiter will provide clear guidance as you move through the interview process.
Undisclosed use of AI not previously discussed with or approved by your Recruiter may impact your candidacy.

About the Team

The Messaging team owns the backbone of Life360's real-time infrastructure — the event streaming and data pipelines that keep millions of families connected. We process billions of events every day across location updates, safety alerts, and the push notifications that make the product feel instant.

We are a small, platform-focused, AI-native team. AI isn't a productivity add-on here — it's how we work. Every engineer on the team directs AI agents as a core part of their daily loop: scaffolding services, drafting Terraform, exploring unfamiliar codebases, writing migration scripts, and reviewing diffs. We move faster and go deeper on hard distributed systems problems because we've built the habits, prompts, and guardrails to make agentic work reliable.

Current initiatives include the MSK-to-Confluent Cloud migration, organization-wide schema registry and Protobuf governance, and the next generation of Life360's streaming services. Our stack is Kafka and Kafka Streams, Spring Boot (Java 21), Go, Protobuf/gRPC, Terraform, and AWS.

About the Job

This is a hands-on senior engineering role for someone who has already made AI a first-class collaborator in their work. You'll design streaming services, write and review code, own production incidents, and ship infrastructure — and you'll do all of it with agents running in parallel alongside you. We're looking for an engineer who already decomposes work into agentic workflows, critiques agent output with real technical authority, and ships production code faster because of it.

You'll help shape the team's technical direction on Kafka-first streaming infrastructure and the next phase of our high-availability roadmap. You'll also help evolve how the team itself works with AI — the prompts, the evals, the review patterns, the escape hatches when agents go sideways.

What You'll Do

• Design, build, and operate streaming services on Kafka, Spring Boot, and Spring Cloud Stream — directing agents to scaffold, test, and iterate, and owning the outcome end-to-end.
• Develop and manage Kafka connectors for data integration (DynamoDB, S3, NSQ, custom sinks/sources) and the SMT chains that keep them honest.
• Own schema management and evolution across Protobuf, Schema Registry, and multi-language code generation — including the Gradle/Nexus publishing pipelines that back it.
• Drive platform migrations (MSK → Confluent Cloud, NSQ → Kafka) including dual-cluster consumer patterns, VPC peering, and cutover playbooks.
• Build monitoring, alerting, and operational tooling (DataDog, PagerDuty, Prometheus) that catch problems before pages fire.
• Write infrastructure as code in Terraform, ship it through CI/CD, and participate in the on-call rotation and incident response for the services you own.
• Work AI-natively as the default mode of operation. Run multiple agents in parallel. Write prompts with real context and constraints. Review every diff like you wrote it yourself. Know when to throw the agent's output out and do it by hand.
• Evolve the team's AI-native practices — prompt libraries, evals, review rituals, and the guardrails that make all of it safe at production scale.
• Mentor teammates, raise the bar on technical standards, and contribute to the team's API design, data contracts, and integration patterns.

Compensation

For candidates based in the US, the salary range for this position is $148,000 to $216,500 USD. For candidates based out of Canada, the salary range is 171,500 to $201,000 CAD. 

Note: We take into consideration an individual's background and experience in determining final salary — therefore, base pay offered may vary considerably depending on geographic location, job-related knowledge, skills, and experience. The compensation package includes a wide range of medical, dental, vision, financial, and other benefits, as well as equity.

What We're Looking For

Technical foundation

• 6+ years of backend software engineering experience.
• Strong proficiency with Java and Spring Boot — this is our primary stack and you should be comfortable reading, writing, and debugging it without assistance.
• Production experience with Apache Kafka or a comparable distributed streaming platform (Pulsar, Kinesis, Pub/Sub).
• Solid grounding in distributed systems concepts: consistency, fault tolerance, replication, delivery semantics, and data durability tradeoffs.
• Comfortable with AWS (or equivalent cloud) and containerized deployments on Kubernetes.
• Hands-on experience with Terraform or comparable IaC for real, multi-environment infrastructure.

AI-native working style

Specifically, we're looking for:

• Prompting excellence — you give agents context, constraints, and expected outcomes. You don't type "do X" and hope.
• Critical validation — you can explain every line the agent wrote, identify where it succeeded and where it fell short, and correct it. You treat AI output as a draft from a smart junior, not an oracle.
• Agentic decomposition — you break ambiguous problems into discrete, verifiable sub-tasks that an agent can actually execute, rather than handing it a blob of intent.
• Parallel workstreams — you run multiple agents or sessions concurrently on independent tasks instead of hand-holding one at a time.
• Troubleshooting with AI, not around it — when an agent hallucinates an API, suggests a deprecated library, or produces code that compiles but is wrong, you diagnose and recover. The interview is designed so things will go wrong; how you get unstuck is a signal.
• Technical authority — you understand the underlying tech (Kafka internals, Protobuf wire format, JDBC, SASL_SSL auth, partitioning semantics) well enough to catch the agent when it's confidently wrong.

What matters most to us

• Problem-solving mindset — you structure ambiguous problems precisely before reaching for a tool, AI or otherwise.
• Ownership — you take a feature from design through production and through the 3 a.m. page that follows.
• Direct, respectful communication — you can explain technical tradeoffs clearly, push back when you disagree, and change your mind when the evidence changes.
• Collaborative — you work well across teams and value perspectives that aren't your own.

Nice-to-have

• Go experience (we use it for CLI tools and some services).
• gRPC and Protocol Buffers in production, including schema evolution strategies.
• Stream processing frameworks — Kafka Streams, Flink (SQL or DataStream).
• Confluent Platform or Confluent Cloud specifics (Schema Registry, Connect, ksqlDB, Stream Governance).
• CI/CD with GitHub Actions, artifact management (Maven, Nexus).
• Observability tooling — DataDog, Prometheus, Grafana.
• Prior experience on large-scale platform migrations or infrastructure modernization programs.
• Building or running evals for LLM-based workflows, prompt libraries, or agent tooling at your current or previous team.

Our Benefits

• Competitive pay and benefits.
• Medical, dental, vision, life and disability insurance plans (100% paid for US employees). Supplemental medical and dental plans for Canadian employees.
• 401(k) plan with company matching program in the US and RRSP with DPSP plan for Canadian employees.
• Employee Assistance Program (EAP) for mental wellness.
• Flexible PTO and 12 company-wide days off throughout the year.
• Learning & Development programs.
• Equipment, tools, and reimbursement support for a productive remote environment.
• Free Life360 Platinum Membership for your preferred circle.

Life360 Values

Our company's mission-driven culture is guided by our shared values to create a trusted work environment where you can bring your authentic self to work and make a positive difference:

• Be a Good Person — We have a team of high-integrity people you can trust.
• Be Direct With Respect — We communicate directly, even when it's hard.
• Members Before Metrics — We focus on building an exceptional experience for families.
• High Intensity High Impact — We do whatever it takes to get the job done.

Our Commitment to Diversity

We believe that different ideas, perspectives and backgrounds create a stronger and more creative work environment that delivers better results. Together, we continue to build an inclusive culture that encourages, supports, and celebrates the diverse voices of our employees. It fuels our innovation and connects us closer to our customers and the communities we serve. We strive to create a workplace that reflects the communities we serve and where everyone feels empowered to bring their authentic best selves to work.

We are an equal opportunity employer and value diversity at Life360. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status or any legally protected status.

We encourage people of all backgrounds to apply. We believe that a diversity of perspectives and experiences create a foundation for the best ideas. Come join us in building something meaningful. Even if you don't meet 100% of the below qualifications, you should still seriously consider applying!

About Life360

Life360’s mission is to keep people close to the ones they love. Our category-leading mobile app, Tile tracking devices, and Pet GPS tracker empower members to protect the people, pets, and things they care about most with a range of services, including location sharing, safe driver reports, and crash detection with emergency dispatch. Life360 serves approximately 91.6 million monthly active users (MAU), as of September 30, 2025, across more than 180 countries.

Life360 delivers peace of mind and enhances everyday family life with seamless coordination for all the moments that matter, big and small. By continuing to innovate and deliver for our customers, we have become a household name and the must-have mobile-based membership for families (and those friends who are basically family).

Life360 has more than 500 (and growing!) remote-first employees. For more information, please visit life360.com.

Life360 is a Remote-First company, which means a remote work environment will be the primary experience for all employees. All positions, unless otherwise specified, can be performed remotely (within the US) regardless of any specified location above. 

We are AI Native 

We are building an AI native company where AI is an integral part of how we build and operate. AI tool usage during interviews varies by role. You may be asked to demonstrate proficiency with AI tools, discuss how you leverage AI, or complete interview exercises without AI assistance. Your Recruiter will provide clear guidance as you move through the interview process.
Undisclosed use of AI not previously discussed with or approved by your Recruiter may impact your candidacy.

About The Team

The Finance Data Team sits at the intersection of Finance & Accounting teams and Life360’s data. We provide the data ingestion / processing / reporting / egress needed by our partner teams in Finance & Accounting to enable their work and ensure SOX compliance with rigor. We push the envelope on how work is done through implementation of AI tools and capabilities to enhance our own pace of development and capabilities that we deliver to our stakeholders.

We are hiring a bar-raising Staff Data Engineer to drive our ingress / egress capabilities and build cross-cutting capabilities to drive developer experience and security. This role requires someone who can step into ambiguity, make sound architectural decisions, eliminate operational fragility, and establish an engineering discipline that others adopt.

You will serve as a technical reference point - shaping standards, influencing cross-team architecture, and driving initiatives to clear, production-ready outcomes. We value engineers who are direct, collaborative, and proactive in surfacing risks early, while helping build a team culture where high standards and psychological safety coexist.

About the Job

The Life360 Finance Data Team works as the integrator for numerous systems - bringing data into the Finance Data Warehouse, transforming it, and pushing it to its relevant destinations (reporting, data asset deliverables, tools, etc).  To support our role we are continuously building and enhancing our system - adding new data, new transformations, and new tooling to improve developer velocity and ‘buy down’ overhead costs associated with maintaining our system.

As a Staff Data Engineer you will drive forward the:

• Data ingestion suite - a mix of capabilities ranging from Fivetran to completely custom connectors that bring data into our warehouse and monitor for data quality.
• Data transformation suite - enhancing our dbt environment (dbt core) and the suite of tools that we leverage to build data models, semantic models, and other interfaces.
• Data egress suite - a mix of capabilities that allow us to push data to its end destinations.
• CI/CD pipelines and other tools / capabilities to enhance the developer experience and velocity.
• Infrastructure and networking behind our warehouse and related connectors.
• Databricks configuration and capabilities.
• Security posture and access controls.

The ideal candidate:

• They have spent years building out data platforms / infrastructure as well as creating ingress / egress data frameworks that are used in pipelines.  They have tackled numerous challenges and found novel solutions to problems for data ingestion, processing, and egress.
• They have learned how to leverage LLMs for development velocity and analytics - not just asking it to write the code but leveraging the tools to support their development under clear guidance and accepts ownership of the work produced as their own.
• They have learned to think about scalability / velocity / experience of future development and not just shipping the current project.
• They are part software engineer, part data integration engineer, and part data platform engineer.
• They adhere to the controls / procedures / separation of duties necessary to maintain our SOX compliance.

We are looking for someone with strong engineering depth who demonstrates ownership, decisiveness, and the ability to elevate both the system and the team around them.

For candidates based in the US, the salary range for this position is $190,000 to $280,500 USD. For candidates based out of Canada, the salary range for this position is $220,000 to $260,000 CAD. We take into consideration an individual's background and experience in determining final salary; therefore, base pay offered may vary considerably depending on geographic location, job-related knowledge, skills, and experience. The compensation package includes a wide range of medical, dental, vision, financial, and other benefits, as well as equity.

AI / LLM Usage

The Finance Data Team leverages LLM’s to support code generation, analysis, and other use cases.

• Cursor / Claude Code.
• Other tools (Wispr Flow, Claude & Claude Cowork, Gemini / Codex).

Your experience with AI / LLM usage should include managing code generation with a close eye on quality, standards, and testing - owning the outputs as your own.  Your work with and ability to leverage these tools will drive your velocity and ability to effectively work within our environment.

What You’ll Do

• Architect and evolve scalable data ingestion and egress frameworks and pipelines that are well tested and offer strong data quality monitoring. 
• Architect and evolve our CI/CD processes - enhancing the testing environment and observability (such as building LLM-driven reviews with context awareness through data diffing, lineage analysis / downstream impact analysis, and general context).
• Architect delivery architecture of data assets to external team partners to reduce manual operational overhead associated with month end close.
• Enhance our Claude Code / LLM development support capabilities - creating tools / skills / agents that give our LLMs more context and help us continually improve their abilities to debug, create code, and maintain systems.
• Enhance our security posture in our AWS / Databricks environment.
• Design and implement distributed data processing systems using Spark and Databricks on AWS.
• Establish clear ingestion and integration boundaries that eliminate single points of failure.
• Proactively surface risks, dependencies, and tradeoffs before they impact delivery.
• Produce clear technical artifacts and recommendations for stakeholders and leadership.
• Design logical and physical data models balancing flexibility, performance, governance, and scalability.
• Partner closely with the Analytics Engineers on the Finance Data Team to support high-quality downstream data modeling & reporting.
• Harden pipelines with monitoring, alerting, SLAs, and recovery mechanisms.
• Mentor engineers and elevate distributed systems rigor across the team.

What We’re Looking For

• 8+ years designing and operating high-volume distributed data systems in production.
• Deep expertise with a cloud data platform (Databricks strongly preferred) and AWS from an infrastructure / services architecture, deployment, and ownership perspective.
• Strong proficiency in Python, SQL, and Spark for large-scale processing.
• Strong proficiency with modern CI/CD practices (creating GitHub Actions, writing Terraform code to manage infrastructure in Databricks / Airflow / AWS / and others).
• Hands-on experience with dbt from an infrastructure / deployment perspective and understanding of how platform decisions impact downstream modeling.
• Strong grasp of data modeling, partitioning strategies, storage formats, and analytical workload optimization.
• Experience with Airflow and data flow orchestration.
• Experience with networking challenges in data ingestion (e.g., VPC peering, firewall traversal, API rate limiting, cross-AWS account access, etc.)
• Able to effectively leverage / oversee LLM-supported code development while maintaining a high quality bar.
• Demonstrated experience with AI tools to support / enhance development - Claude Code, Cursor, etc.
• Demonstrated ability to independently scope ambiguous problems and drive them to decisive outcomes.
• Track record of proactively escalating risks and closing long-running efforts with clear recommendations.
• Experience defining ingestion validation standards and implementing data quality controls.
• Proven ability to reduce operational fragility and eliminate single points of failure.
• Strong systems design skills across distributed and event-based architectures.
• Demonstrated technical leadership influencing cross-team architectural decisions.
• Excellent communication skills across engineering, analytics, product, and executive stakeholders.
• BS in Computer Science, Engineering, Mathematics, or equivalent experience.

Our Benefits

• Competitive pay and benefits.
• Medical, dental, vision, life and disability insurance plans (100% paid for US employees). We offer supplemental plans for medical and dental for Canadian employees.
• 401(k) plan with company matching program in the US and RRSP with DPSP plan for Canadian employees.
• Employee Assistance Program (EAP) for mental wellness.
• Flexible PTO and 12 company wide days off throughout the year.
• Learning & Development programs.
• Equipment, tools, and reimbursement support for a productive remote environment.
• Free Life360 Platinum Membership for your preferred circle.

Life360 Values

Our company’s mission-driven culture is guided by our shared values to create a trusted work environment where you can bring your authentic self to work and make a positive difference 

• Be a Good Person - We have a team of high-integrity people you can trust. 
• Be Direct With Respect - We communicate directly, even when it’s hard.
• Members Before Metrics - We focus on building an exceptional experience for families. 
• High Intensity, High Impact - We do whatever it takes to get the job done. 

Our Commitment to Diversity

We believe that different ideas, perspectives, and backgrounds create a stronger and more creative work environment that delivers better results. Together, we continue to build an inclusive culture that encourages, supports, and celebrates the diverse voices of our employees. It fuels our innovation and connects us closer to our customers and the communities we serve. We strive to create a workplace that reflects the communities we serve and where everyone feels empowered to bring their authentic best selves to work.

We are an equal opportunity employer and value diversity at Life360. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status or any legally protected status.  

We encourage people of all backgrounds to apply. We believe that a diversity of perspectives and experiences creates a foundation for the best ideas. Come join us in building something meaningful. Even if you don’t meet 100% of the qualifications above, you should still seriously consider applying!

#LI-Remote

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Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

The Forward Deployed Engineering (FDE) team exists to solve the hardest problems our most complex enterprise users face, and to turn those solutions into platform capabilities that scale to everyone. We work across Revenue Suite, Payments, and adjacent products. This is not a support function. It is an engineering team that sits at the boundary between Stripe's platform and the real-world complexity of how large enterprises actually use it.

The traditional FDE playbook, one engineer per user who manually rebuilds context every rotation, is how every infrastructure company has done it for a decade. It does not scale. We are building something different: an agent-augmented model where AI handles the context-heavy, structured work (integration mapping, state reconciliation, infrastructure shadow testing, diagnostics) and human FDEs focus on the parts that require engineering judgment, product thinking, and direct user relationships. The goal is to build engineering muscle that lets us serve every strategic user through the platform, not just the handful we can staff individually.

We've proven the approach with some of the world's most demanding enterprise users, delivering measurable auth rate improvements, unblocking critical platform migrations, closing multi-product integration gaps, and driving real revenue. Now we're scaling the model. If you want to solve hard user problems, build reusable platform solutions, and help shape how forward deployed engineering works as a discipline, this is the team. 

What you’ll do

As an Engineer on the RFA Forward Deployed Engineering team, you will:

• Work alongside AI agents to serve users at scale. This is central to how our team operates. AI agents maintain real-time integration maps, run shadow tests against user setups, and perform automated state reconciliation between Stripe and user systems. Your job is the work that requires an engineer: making judgment calls on ambiguous problems, building relationships with user engineering teams, making product decisions, and designing solutions. You will also help shape the tooling itself, identifying what should be automated and what needs to stay human.
• Engage directly with users. You will work with Stripe's most strategic enterprise users to understand their revenue, billing, and payments requirements. You translate what you learn into technical solutions, and you bring that user reality back to product teams. This is a genuinely user-facing role, not user-facing in the "I read a dashboard" sense.
• Build across product boundaries. You will design and deploy products and solutions that address product-market fit gaps, not just in Billing but across multi-product boundaries (Payments + Invoicing + Global LPMs). You embed within Stripe product engineering teams to co-develop the highest-leverage capabilities.
• Build reusable solutions, not one-off fixes. Contribute to a customization framework for RFA and adjacent products: tailored billing logic, financial workflows, integrations (custom metering, product catalog integrations, checkout flows). Build patterns and blueprints that scale beyond the individual engagement.
• Provide architectural guidance. Review user architectures, advise on best practices, and optimize integration and performance for complex enterprise environments. Contribute to a growing library of architectural patterns for the field.
• Resolve critical technical challenges. Diagnose and fix complex product/engineering problems across the stack. Identify systemic improvements that prevent recurrence and improve platform stability.
• Inform the product roadmap. The integration gaps, migration friction, and multi-product failures you surface directly shape Stripe's product strategy. You advocate for what users actually need based on what you've seen firsthand.
• Raise the bar on engineering. Improve engineering standards, tooling, and processes within the team. Help build for sustainability as the team grows.

Who you are

You're a strong engineer who also thinks like a product person. You're comfortable with ambiguity, you'd rather talk to a user than read a spec, and you care about whether the thing you built actually solved the problem. Think: early engineer at a startup who played PM, did product discovery, partnered with users, and shipped. You're also interested in working at the frontier of agent-augmented engineering, not just using AI tools but helping define how an engineering function operates alongside them.

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• 5+ years of experience in software engineering, with a strong focus on backend systems.
• Proven ability to design, build, and maintain highly available, scalable, and secure systems.
• Strong command of distributed systems, API design, and data modeling.
• Excellent problem-solving skills and the ability to quickly grasp complex technical and business domains.
• Clear communicator, both written and verbal, with technical and non-technical stakeholders including external users.
• Track record of working well in collaborative environments with product managers, TPMs, and other engineers.
• Willingness to engage directly with users to understand requirements and co-develop solutions. This is a core part of the role.
• Willingness to travel (~20-30%) to Stripe sites (Toronto, SF, Seattle) and user locations.

Preferred qualifications

• Experience with financial automation or billing products (e.g., Stripe Billing, Tax, Revenue Recognition, or similar).
• Experience with multi-product integration: stitching together payments, invoicing, billing, and related systems.
• Familiarity with extensibility models, custom solution frameworks, or platform development.
• Experience working with large enterprise users or in a customer-facing engineering role.
• Prior experience in a fast-paced, ambiguous environment where priorities shift based on user needs.
• Interest in or experience with AI-augmented engineering: working with AI agents, LLM-powered tooling, or building workflows where humans and AI collaborate.

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

The Supportability Evaluation team acts as stewards of the financial ecosystem. Our mission is to protect Stripe’s reputation with our global financial partners by architecting highly precise, automated supportability controls. We develop the AI/ML models and systems that detect and action supportability violations in real-time. We're responsible for building high-fidelity detection engines that ensure our merchants remain compliant across the globe, balancing the scale of millions of users with the surgical precision required by the world’s largest financial institutions.

What you’ll do

As a Machine Learning Engineer in Supportability, you will be responsible for designing, building, training, evaluating, deploying, and owning AI/ML models in production. You will work closely with software engineers, machine learning engineers, product managers, and data scientists to operate Stripe’s ML powered systems, features, and products. You will also have the opportunity to contribute to and influence AI/ML architecture at Stripe and be a part of a larger community.

Responsibilities

• Design state-of-the-art AI/ML models and large scale systems for detection and decisioning for Stripe products based onAI/ML principles, domain knowledge, and engineering constraints
• Drive the expansion of Stripe's largest LLM-based system, scaling its usage and integrating new capabilities through agentic approaches or supervised learning.
• Rapidly prototype new AI/ML-based approaches to achieve key business goals.  
• Develop processes to train and evaluate models in offline and online environments
• Integrate models into production systems and ensure their scalability and reliability
• Collaborate with product and strategy partners to propose, prioritize, and implement new product features
• Engage with the latest developments in AI/ML and take calculated risks in transforming innovative ideas into productionized solutions
• Explore cutting-edge AI/ML techniques and evaluate their potential to solve business problems

Who you are

We are looking for ML Engineers who are passionate about building AI/ML and AI systems that touch the lives of millions. You have experience building and evaluating advanced AI/ML models, and deploying them to production. You are comfortable with ambiguity, love to take initiative, have a bias towards action, and thrive in a collaborative environment.

Minimum requirements

• 2+ years of industry experience building and shipping AI/ML systems in production
• Proficient with AI/ML libraries and frameworks such as PyTorch, TensorFlow, XGBoost, as well as Spark 
• Knowledge of various AI/ML algorithms and model architectures
• Hands-on experience in designing, training, and evaluating machine learning models
• Hands-on experience in productionizing and deploying models at scale
• Experience rigorously evaluating model performance, including cleaning data, and working with data-generating processes to improve signal and reduce noise in high-noise datasets.
• Proficiency in creatively applying modern machine learning techniques and Generative AI models to solve complex business problems.

Preferred qualifications

• MS/PhD degree in AI/ML or related field (e.g. math, physics, statistics)
• Experience with DNNs including the latest architectures such as transformers and LLMs
• Experience working in Java or Ruby codebases
• Proven track record of building and deploying AI/ML systems that have effectively solved ambiguous business problems
• Experience with online experimentation such as A/B testing or multi-armed bandits.
• Experience with model calibration

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

Web Presence and Platform is organized into two pillars, each of which is grouped into pods that focus on the central tenets of Stripe's public mission. The Presence pillar creates industry-leading designs for Stripe’s front door surfaces, educating customers about the power of our platform, sharing Stripe’s ideas and expertise with the public, and driving adoption. The Platform pillar builds the internal machinery that powers these surfaces, and is responsible for making our websites fast, stable, and easy to update.

Together we design and build stripe.com and other sites that amount to what is, for many, their first impression of Stripe. As such, WPP offers exciting opportunities to have a major impact on Stripe’s success. We want to make every pixel count, we want it to be enthralling, and we want to help other Stripes seamlessly benefit from our systematic work.

While the team's mission anchors to web surfaces, this role lives deeper in the stack. You will be the engine behind the experiences rather than the pixel-level presentation — APIs, data pipelines, model orchestration, and service reliability that make LLM-driven user experiences possible at scale.

What you’ll do

The Expansion pod brings creativity and executional rigor to attracting new prospects and driving conversion, focusing on user journeys, interactive and highly polished tools for users, and building targeted experiences for our global users.

As a backend engineer you will architect and build the server-side systems and LLM orchestration layers that power intelligent, dynamic user experiences across acquisition journeys. You will design the APIs, data pipelines, and inference infrastructure behind delightful and original interactive tools and resources that attract users. You will collaborate deeply across design, engineering, and cross-functional teams and work across teams and tech stacks to create new site capabilities — with a specific focus on integrating large language models into production-grade services that are reliable, performant, and safe.

This is not a research or ML training role. You will be responsible for wiring LLMs into real user-facing products: managing prompt pipelines, handling model routing and fallback logic, implementing guardrails and output validation.

Responsibilities

• Develop and implement the tooling and platforms to support interactive content tools (e.g., calculators, generators, templates) that provide utility to current and prospective businesses.
• Utilize a user-first mindset to implement feedback mechanisms for continuous improvement of content and product offerings.
• Design and build integrations to third-party software and create seamless workflows across these tools to unleash their full potential to the rest of Stripe.
• Ensure reliability, security, and responsible AI practices across all LLM-driven features, including implementing content filtering, PII handling, rate limiting, graceful degradation, and output guardrails.
• Work with a small team of technically sophisticated engineers who put users first.

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• 5+ years of backend development experience, with emphasis on building APIs and services that power user-facing experiences
• Experience writing clear, elegant code in a team environment
• Familiarity with LLM APIs and concepts — prompt engineering, token management, embedding models, retrieval-augmented generation, or function calling. You don't need to be a researcher, but you should understand how these models work well enough to build production systems around them.

• Experience building and operating distributed backend systems — you're comfortable with service-oriented architectures, async processing, caching layers, and monitoring/alerting in production.
• Passion for engineering solutions focused around growth hacking & enablement 
• Excellent verbal and written communication

Preferred qualifications

• Proven ability to stitch different services and processes together even if you have not worked with them before
• Experience in developing interactive tools and integrating them with existing systems.
• Experience building highly complex interactive tools, including state management and data fetching
• Experience with data pipeline orchestration (Airflow, Dagster, Temporal, or similar) and structured output parsing from LLMs
• Experience with prompt versioning, A/B testing model outputs, or building model gateway/routing layers that allow teams to swap or compare providers (e.g., OpenAI, Anthropic, open-source models)
• Proficiency with React, with a focus on interactions, animation, performance, and polish
• Experience with A/B testing, synthetic monitoring, or accessibility testing

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

Stripe processes over $1T in payments volume per year, which is roughly 1% of the world’s GDP. The tremendous amount of data makes Stripe one of the best places to do machine learning. The ML Infra team builds services and tools that power every step in the ML lifecycle, including data exploration, feature generation, experimentation, training, deploying, serving ML models, and building LLM applications. With the phenomenal developments happening in the field of AI, we are positioned to accelerate the adoption of AI/ML across all parts of the company by building highly scalable and reliable foundational infrastructure.

What you’ll do

You will work closely with machine learning engineers, data scientists, and product engineering teams to enable seamless end-to-end experience in building solutions across data, analytics, and AI/ML platforms. You will build the next generation of ML Infra services and major new capabilities that substantially improve ML development velocity and MLOps maturity across the company.

Responsibilities 

• Designing and building scalable, reliable, and secure services for notebooks, ML model training, experimentation, serving, and LLM applications across multiple regions. 
• Creating services and libraries that enable ML engineers at Stripe to seamlessly transition from experimentation to production across Stripe’s systems. 
• Working directly with product teams and ML engineers to improve their day-to-day productivity. 
• Taking ownership of and finding solutions for technical and product challenges by working with a diverse set of systems, processes, and technologies.

Who you are

We’re looking for people with a strong background or interest in building successful products or systems; you’re passionate about solving business problems and making impact, you are comfortable in dealing with lots of moving pieces; and you’re comfortable learning new technologies and systems. You are comfortable working with other Stripe teams across the US and Canada.

Minimum requirements

• 2+ years of professional software development experience with a solid background on service oriented architecture and large-scale distributed systems
• Experience working through the full life cycle of software development, from talking to users, to design and implementation, to testing and deployment, to operations
• Experience working on production ML platforms, MLOps solutions, or building LLM applications
• Experience running operations for high availability, low latency systems
• Experience partnering with other teams to drive business outcomes
• A sense of pragmatism: you know when to aim for the ideal solution and when to adjust course

Preferred qualifications 

• Experience building and shipping production AI agents
• Familiarity with the LLMs and LLM Frameworks
• Experience training and shipping machine learning models to production to solve critical business problems

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

The Support Experience engineering organization builds and improves Stripe’s user support from end to end: how users get help within our products, how they get in touch with us when they have questions, and how our teams use internal tools to answer those questions. We’re accountable for the quality and reliability of this support stack and we use data and firsthand user research to continuously improve it. 

Providing great support to users of all sizes is culturally important to everyone at Stripe. We are a group of friendly, user-oriented engineers that partner closely with Stripe’s world-class design, product, and operational teams. This includes the external-facing support interfaces (support.stripe.com), content, entry points, internal tooling, case routing, and helping product teams across the company reduce support volume by improving our products. We are also using the latest generative AI technologies to re-imagine support experiences, and are developing AI assistants for Stripe’s users and internally to help our operations teams be more productive.

What you’ll do

As a Machine Learning Engineer on the Support Experience team, you'll play a crucial role in enhancing our self-serve support experiences. You will be responsible for designing, building, training, evaluating, deploying, and owning ML models in production. For example, we apply LLMs to answer user questions with conversational agents and personalize product documentation, and are building automated systems to solve complex user problems. You will work closely with software engineers, machine learning engineers, product managers, and data scientists to operate Stripe’s ML powered systems, features, and products. You will also have the opportunity to contribute to and influence ML architecture at Stripe and be a part of a larger ML community. 

Responsibilities

• Design  and implement state-of-the-art ML models and large scale ML systems for enhancing self-serve support capabilities, balancing ML principles, domain knowledge, and engineering constraints
• Develop and optimize contextual conversation models and ML-powered resolution flows for common support scenarios, using tools such as PyTorch, TensorFlow, and XGBoost
• Create and refine pipelines for training and evaluating models in both offline and online environments, with a focus on improving support quality and user satisfaction
• Implement ML features that streamline information collection and processing for support agents, enhancing overall support efficiency
• Collaborate with product, strategy, and content teams to propose, prioritize, and implement new AI-driven support features and improve answer capabilities
• Stay current with the latest developments in ML/AI, particularly in natural language processing and conversational AI, and apply innovative ideas to improve support experiences

Who you are

We are looking for ML Engineers who are passionate about building ML systems that touch the lives of millions. You have experience developing efficient feature pipelines, building advanced ML models, and deploying them to production. You are comfortable with ambiguity, love to take initiative, have a bias towards action, and thrive in a collaborative environment.

Minimum requirements

• Bachelor's Degree in ML/AI or related field (e.g. math, physics, statistics)
• 3+ years in AI/ML and backend engineering, including building and operating production ML systems at global scale with stringent SLOs—balancing reliability, latency, and cost—with privacy, security, and compliance by design.
• Deep and up-to-date applied LLM experience: RAG/embeddings, tool use/function calling, agentic planning/orchestration architectures, post-training methods, code generation, benchmarks and evaluations, etc. Familiarity with classical ML methods and common frameworks e.g. Pytorch, TensorFlow.
• Proficient in Python; strong distributed systems and data science fundamentals.
• Experience working closely with product management, design, other engineers, and other cross-functional partners.
• Strong technical leadership and communication: mentoring and elevating engineers, elevating AI/ML awareness and posture within organizations, setting architectural direction, and driving alignment in ambiguity.

Preferred qualifications

• MS/PhD degree in ML/AI or related field (e.g. math, physics, statistics)
• Experience working in Java or Ruby codebases
• Experience designing, deploying, and owning Agentic LLM solutions (e.g., multi-step orchestrators, tool use/function calling) specifically for complex customer support or internal workflow automation.
• Comfortable working with distributed teams across multiple locations and time zones

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

AI is moving fast and Stripe is moving fast to adopt it. But we need to make sure we do all of this safely, and for most of these tools enterprise-grade security isn't just available off the shelf. That's where the AI security team comes in - we are responsible for building and partnering to create the right security primitives to enable Stripe to move fast safely.

This is a team that will be working in the low level components of our AI stack so both infrastructure and security experience are pluses. This space is moving fast so being comfortable with ambiguity and changes in priority are a must.

This is a foundational role — you'd be the first engineer on the team.

What you’ll do

Engineers on this team will do a mixture of partnering and advising with teams building AI infrastructure and products, and building security infrastructure primitives for AI. 

One of our major focuses will be building a security tooling layer that sits in the inference path, providing detection and protection against AI specific threats like prompt injection, jailbreaks, and tool misuse.

Responsibilities

• Build security frameworks integrated with our core AI infrastructure
• Design and implement defenses against AI specific threats like prompt injection and jailbreaks
• Collaborate with other engineering teams to ensure Stripe's AI infrastructure and products are built securely
• Support other engineering teams in integrating security primitives
• Uphold our high engineering standards and improve our codebase and processes
• Design and build systems that help define the state of the art for AI security

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• 5+ years of software development experience
• Experience independently designing and developing medium to large projects
• Experience working collaboratively across multiple engineering teams
• Experience writing high quality code in a major programming language
• Ability to drive clear next steps when working in an ambiguous environment
• Ability to think creatively and reason clearly in a complex problem domain

Preferred qualifications

• Experience developing, deploying, and maintaining reliable infrastructure systems
• Experience in security engineering
• Experience building AI agents or LLM-based systems

Role Summary

We’re looking for a Digital Content & AI Automation Manager to lead our transition to 'Vibe Marketing.' Inspired by the shift toward Vibe Coding, we want to bridge the gap between creative intent and digital execution. You’ll move Okta away from manual tickets and rigid CMS forms toward an agentic, self-service model—building the tools that allow marketers to describe a goal in natural language and see it manifest across our digital ecosystem.

This is a test, learn, build, iterate role. You aren't just managing a stack; you’re building an autonomous engine that empowers every marketer to be a creator.

What You’ll Actually Do

• Build the "Vibe Marketing" tools: Create the workflows and agentic layers that allow non-technical stakeholders to manage and scale digital content across its entire lifecycle using natural language and AI assistance.
• Develop Agentic Support Models: Prototype and deploy AI agents that act as "co-pilots" for Marketing Managers—handling everything from automated tagging and metadata to complex distribution across our headless ecosystem.
• Architect Self-Service Systems: Reduce the "time-to-live" by building modular, reusable content structures that agents can manipulate, moving us beyond the constraints of traditional platforms like Adobe Experience Manager.
• Operate Like a Lab: Run rapid experiments with emerging AI tools and automation platforms. Build scrappy prototypes—not just strategy decks—to prove that "vibe-based" creation works at enterprise scale.
• Partner Across Teams: Bridge the gap between "what if" and "here’s how," working with Marketing, Engineering, and Digital teams to turn agentic concepts into production-ready workflows.

What We’re Looking For

• The "Vibe" Mindset: You understand the shift from "doing the work" to "directing the agents." You’ve followed the Vibe Coding movement and are itching to apply it to Marketing Tech.
• 4–8 Years of Experience: You’ve seen the limitations of legacy CMS architectures and are ready to bypass those bottlenecks by building a modern, agent-led content supply chain.
• Hands-on AI & Automation: You don't just prompt; you build. You have experience with APIs, MCP, LLM orchestration, and connecting tools to create seamless loops.
• Technical Fluency: You aren't a full-stack engineer, but you understand how to navigate enterprise complexity—you're comfortable with structured content, and the logic of how data flows between a headless CMS, an LLM, and the front-end.

#LI - Hybrid

P24086_3333054

Engineering

Engineering at Brex is about building systems that scale with speed and intention. Our teams span Software, Data, Security, and IT, and operate with high autonomy and deep collaboration. We tackle hard technical problems, own our outcomes, and push for excellence at every level — from architecture to deployment. It’s an environment where engineering is a craft, and builders become leaders.

What you’ll do

You will lead an engineering team focused on building the systems and product experiences that power customer activation at Brex,  including onboarding, account setup, verifications, and integrations workflows that help customers realize value quickly. This role requires strategic thinking, operational excellence, technical leadership, and a deep passion for delivering frictionless, AI-enhanced customer journeys. The ideal candidate is an engineering leader with experience scaling user-facing onboarding systems, delivering high-quality product experiences, and partnering deeply across Product, Design, Operations, and GTM teams.

Where you’ll work

This role will be based in our Vancouver office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Take an active role in driving business and product strategies, championing a seamless, intuitive, and efficient onboarding experience.
• Collaborate with cross-functional partners across Product, Design, Operations, and Sales to define priorities and deliver delightful customer activation experiences.
• Leverage AI to reimagine and automate onboarding and implementation workflows, improving speed, personalization, and operational leverage.
• Drive execution of the Onboarding roadmap, ensuring timely, high-quality delivery of systems and features that help customers activate and realize value.
• Lead and manage a team of engineers, including hiring, mentoring, performance management, and establishing strong technical direction.
• Drive continuous improvement in engineering processes, technical architecture, and product quality.
• Foster a culture of innovation, collaboration, accountability, and customer obsession across the team.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 6+ years of software engineering experience with strong technical depth
• 3+ years of experience managing or leading engineers in a high-growth environment.
• Strong technical background and understanding of software development principles.
• Expertise leading full-stack engineering teams delivering end-to-end product experiences.
• Regularly works with cross-functional partners (e.g. Product, Design, Operations, Sales) and excels in driving alignment across stakeholders.
• Data-driven mindset with the ability to evaluate impact, measure funnel performance, and optimize activation metrics.
• Track record building AI-powered product experiences, including LLM-driven automation and personalization.

Bonus points

• Experience with data platforms such as Snowflake, Hex, or similar.
• Experience building systems related to onboarding, implementation, identity, workflow automation, customer lifecycle products, or other customer facing experiences.
• You have started your own technology venture or were an early technical founder/employee. We value entrepreneurial spirit & scrappiness!

Compensation

The expected salary range for this role is $240,000 CAD - $300,000 CAD. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

Your role
As an analytics engineer, you’ll be an integral part of our data analysis and QA team, providing essential data support for our cutting-edge Agentic AI initiatives, specifically with ASR and NLP teams. A key focus will be on leveraging data analysis to identify and drive optimization of the conversational flows and underlying data infrastructure for agentic voice and chat solutions. You will actively seek opportunities to improve the team’s productivity and workflow through automation and process optimization, including implementing automated QA for our agentic systems.

This position reports to the manager of the Data Analysis and QA team and has the opportunity to be based in our Vancouver, Canada Office.

What you’ll do 

• You will work closely with other Agentic AI teams to test and evaluate our Agentic voice and chat solutions.
• You will design and implement data logging and monitoring strategies to capture key analytical insights.
• You will utilize data analysis to identify areas for optimization in the voice bot's conversational flows and data pipeline.
• You will build and maintain data pipelines on Vertex AI pipelines. 
• You will work closely with the AI Platform team to build tooling for data science projects. 
• You will implement automation and processes to improve our workflow. 
• You will create and maintain dashboards (Tableau) and data pipelines (Dataform) that help drive product and business decisions.
• You will contribute to our continuous efforts to enforce data privacy and compliance. 
• You will collaborate with cross-functional teams, including AI, engineering, and product teams.

Skills you’ll bring 

• Bachelor's or Master’s degree in Computer Science, Software Engineering, or related fields.
• 1 - 3 years of working experience with software engineering or data engineering projects. 
• 1 - 3 years of experience with Python, working with GCP, including storage, BigQuery, Compute, Kubernetes, or similar.
• 1 - 3 years of experience with SQL, able to optimize complex SQL queries and build data pipelines. 
• Experience with BI tools such as Tableau. 
• Experience analyzing the performance of conversational AI systems (e.g., voice bots, chatbots) and collaborating with cross-functional teams (AI, Product) on data-driven improvements.
• Experience working with popular LLM frameworks.
• Strong problem-solving and analytical abilities, with the capacity to handle complex technical and analytical problems.

Role Overview 

We are seeking an accomplished Principal Engineer to lead the technical architecture and evolution of our hybrid digital ecosystem. In this pivotal role, you will drive the strategic integration of multi-modal AI into our core infrastructure while architecting an omnichannel platform capable of supporting complex customer journeys. You will balance the adoption of proven third-party AI solutions (OpenAI, Anthropic) with the development of proprietary optimizations where they deliver a competitive advantage. As a technical leader, you will champion a vendor-agnostic, ethically grounded, and Privacy by Design approach to AI implementation.

Key Responsibilities

• Infrastructure Modernization: Lead the roadmap for migrating legacy data pipelines to AI-native architectures. You will design modern data orchestration solutions utilizing Apache Airflow, dbt, and Kafka to replace outdated batch processing with real-time, event-driven flows.
• AI-Native Web Transformation: Define the web infrastructure required for a high-agility ecosystem. Architect the evolution of our Headless CMS environments (AEM, Contentful) and modern frontend frameworks to enable automated page assembly and AI-driven UI components.
• Agentic Pipeline Development: Design and build autonomous pipelines that bridge the gap between design systems, automated component development, and publishing workflows.
• ML & Data Engineering Leadership: Establish standards for RAG, vector databases, and LLM orchestration. Provide architectural guidance for the seamless integration of AI capabilities across headless and omnichannel systems while ensuring consistency, performance, and security.
• Engineering Productivity: Champion the use of AI-assisted coding and engineering productivity tools such as Claude Code and Cursor to accelerate development cycles and optimize architectural decision-making.

Required Qualifications

• Experience: 8–10 years in software engineering, specializing in SaaS platform architecture and distributed systems design.
• Leadership & Advocacy: Excellence in technical diplomacy and stakeholder influence. Proven ability to translate complex AI/Data roadmaps into business value while mentoring senior teams and advocating for architectural best practices.
• Data Orchestration: Strong hands-on experience with Apache Airflow (or similar), Kafka, and dbt to support real-time AI applications.
• AI & Web Convergence: Proven expertise integrating LLMs into production web environments with a focus on agentic workflows and autonomous UI generation.
• Architectural Vision: Deep understanding of headless CMS, composable, and event-driven patterns that allow for programmatic content and UI generation.
• Modern Delivery: Experience with cloud-native technologies (AWS/GCP, Docker, Kubernetes) and a deep expertise in data privacy frameworks and AI ethics.

#LI-Hybrid

#P24079_3413893

Narvar is Growing! We’re building Navi — Narvar’s agentic AI that automates post-purchase resolution for the world’s leading retailers. Hundreds of millions of consumers interact with Narvar every year. Navi is our agentic AI that resolves delivery issues, returns, and refunds through natural conversation — powered by IRIS and 74 billion consumer touchpoints. 

We're looking for senior AI engineers to own this system end-to-end: architecture, model selection, production operations. You'll help decide what gets built and how.

Day-to-day

• Design and build conversational AI agents for returns, claims, and customer service experiences
• Own agent systems from architecture → implementation → evaluation → production operations
• Build RAG / context graph retrieval pipelines that ground agent responses in real company and customer data
• Design agent orchestration for multi-step workflows that interact with identity, risk, order, and loyalty systems
• Create evaluation frameworks to measure task completion, accuracy, safety, and user satisfaction
• Implement guardrails and safety mechanisms — content moderation, hallucination detection, graceful fallbacks
• Integrate conversational experiences across web, mobile, SMS, and email channels
• Make real decisions around prompt design, model selection, latency/cost/quality tradeoffs, and failure modes
• Collaborate with product, design, and ML teams to build systems that are technically sound and product-aware

What We’re Looking For

We care more about judgment and ownership than credentials.

You’re likely a strong fit if you:

• Have shipped conversational AI or agent-based systems used by real users in production
• Have built production systems on top of LLM APIs and agent frameworks — not just prompt playgrounds, but real integrations involving tool orchestration, context management, and reliability at scale
• Have a point of view on model selection tradeoffs — when to use frontier APIs vs. open-weight models (Qwen, Llama, Mistral), and understand the cost, latency, privacy, and capability tradeoffs of each
• Understand prompt engineering beyond basics: structured outputs, few-shot learning, chain-of-thought, tool calling
• Have built context graph pipelines that go beyond naive retrieval — entity resolution, relationship modeling, and dynamic context assembly from structured and unstructured data
• Have designed agent architectures that use function calling, tool execution, or multi-step reasoning
• Have strong programming skills in Python or TypeScript
• Have experience building and integrating APIs and backend services
• Are comfortable reasoning about evaluation, safety, and reliability in non-deterministic systems
• Take initiative naturally and are comfortable operating with ambiguity

Bonus points

These aren’t hard requirements, but strong indicators:

• You’ve worked in startup or high-ownership environments
• You’ve built and operated AI systems in production, including monitoring and incident response
• You’ve evaluated and iterated on LLM systems for accuracy, hallucination, latency, and cost
• You’ve built or integrated MCP servers or similar tool-use infrastructure
• You’ve influenced technical direction by earning trust, not by mandate
• You use modern tooling (including AI-assisted development workflows) to increase leverage, not outsource thinking

(Note: we care about outcome and judgment, not how flashy your tools are.)

Why AI at Narvar?

Because post-purchase is one of the highest-leverage applications of conversational AI.

We’re building AI agents where:

• The problem space is well-defined but complex — returns, claims, and support have clear business logic but messy real-world edge cases
• Scale is real — hundreds of millions of consumer interactions per year across major global retailers
• Impact is measurable — resolution rates, customer satisfaction, cost savings, not vanity metrics
• The work is greenfield — you’re not maintaining a legacy chatbot, you’re building the next generation

You’ll help define where and how AI agents should operate, not just implement someone else’s spec.

Why Narvar ( from an Engineer's perspective?)

• Real scale, real customers, real consequences
• Startup-level ownership with platform-level impact
• Teams that value thinking, judgment, and responsibility
• Low ego, high trust, and room to do your best work

Why Narvar?

We're on a mission to simplify the everyday lives of consumers. Post-purchase is a critical phase of the customer journey. That's why we created Narvar - a platform focused on driving customer loyalty through seamless post-purchase experiences that allow retailers to retain, engage, and delight customers. If you've ever bought something online, there's a good chance you've used our platform!

From the hottest new direct-to-consumer companies to retail’s most renowned brands, Narvar works with GameStop, Neiman Marcus, Sonos, Nike, and 1300+ other brands. With hubs in San Francisco, Atlanta, London, and Bangalore, we've served over 125 million consumers worldwide across 10+ billion interactions, 38 countries, and 55 languages.

Pioneering the post-purchase movement means navigating into the unknown. Our team thrives on this sense of adventure while nurturing a mindset of innovation. We're a home for big hearts and we leave our egos at the door. We work hard but we always make time to celebrate professional wins, baby showers, birthday parties, and everything in between.

We are an equal-opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

#LI-BB1

#LI-Remote

See yourself at Twilio

Join the team as Twilio’s next Staff Product Manager - Core Commerce Platform

About the job

Twilio is seeking an intensely curious Staff Product Manager to lead the evolution of our Core Commerce Platform into a highly productized, extensible engine that powers Twilio’s global revenue. You won't just be managing a billing system; you will be architecting a standardized platform-as-a-service that enables internal application teams to launch, price, and scale their products with zero friction. This platform is the source of truth for the entire quote-to-cash lifecycle—responsible for high-throughput metering, complex real-time rating, and the generation of clear, accurate invoices that reinforce customer trust.

Responsibilities

In this role, you’ll bring and develop:

• Master Commerce Domains: Leverage deep expertise in catalog management, subscriptions, billing, invoicing, revenue recognition, and tax compliance to build robust, scalable financial systems.

• Define Platform Strategy: Architect the roadmap for a "commerce-as-a-service" model by developing primitives (metering, rating, and entitlement APIs) that enable internal teams to launch products with minimal bespoke engineering.

• Enable Internal Tenants: Treat Twilio’s internal product and operations teams as primary customers by designing the self-service tools, SDKs, and documentation necessary for independent onboarding to the platform.

• Ensure Usage Fidelity: Own the "event-to-invoice" data lifecycle by architecting systems that transform high-volume usage data into transparent invoices, ensuring rating logic is perfectly mirrored in customer dashboards.

• Productize Compliance: Partner with Finance, Compliance, and Accounting to build automated revenue recognition and geography-aware tax hooks into the platform core to ensure every transaction is audit-ready by default.

• Champion Accuracy & Trust: Drive platform initiatives that provide customers with granular visibility into their usage, reducing billing inquiries and fostering long-term trust through financial integrity.

• Bridge Cross-Functional Gaps: Act as the strategic link between Engineering, Finance, and GTM by translating complex financial requirements into scalable technical specifications and communicating platform guardrails early.

• Integrate AI Capabilities: Embed AI into the commerce platform, such as, billing optimization, anomaly detection, rating logic, and automating internal administrative and reporting activities.

• Lead Forensic Discovery: Conduct deep-dive investigations into the most complex parts of the commerce lifecycle, untangling legacy systems and technical debt to provide the organization with clear paths forward.

• Embed Data-Driven Decisioning: Drive system reliability and business outcomes by using analytics to guide prioritization and fostering a culture of continuous experimentation and learning.

• Technical Mentorship: While an individual contributor role, you will "raise the bar" for the PM org, mentoring PMs on technical product discovery, tracking communication and execution.

Qualifications 

Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table!

*Required:

• 8+ years of industry experience.
• 5+ years of Product Management experience, with at least 3 years focused on commerce, billing, or financial platforms at scale
• Demonstrated ability to lead complex cross-functional initiatives across engineering, finance, risk, and operations.
• Strong technical acumen with experience in APIs, extensible platforms, and complex system design.
• Data-driven decision maker with a track record of defining KPIs and measuring platform success.
• Excellent communication and executive-level stakeholder management skills.
• Experience with SaaS, large-scale platforms, or multi-product ecosystems.
• Deep experience with Agile and related agile tooling, such as, Jira
• Bachelor's degree or equivalent experience

Desired:

• Platform Leadership: Previous leadership of platform migrations or unification efforts.
• ERP & Financial Integration: Experience integrating core billing engines with downstream financial systems like NetSuite, SAP, or Workday for automated revenue recognition.
• Global Tax Compliance: Familiarity with global tax engines (e.g., Avalara, Vertex) and the regulatory requirements of "Invoiced Billing" in international markets (VAT, GST, etc.).
• AI/ML Product Literacy: Experience identifying and implementing AI-driven solutions for financial or data-heavy domains, such as predictive revenue forecasting, automated discrepancy resolution, or LLM-integrated developer documentation.
• SaaS/CPQ Knowledge: Familiarity with the "Quote-to-Cash" ecosystem, including CPQ (Configure, Price, Quote) tools and how they interface with a core catalog.

Location

This role will be remote and based in Ontario, British Columbia or Alberta, Canada.

Travel 

We prioritize connection and opportunities to build relationships with our customers and each other. For this role, you may be required to travel occasionally to participate in project or team in-person meetings.

What We Offer

Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location. Based on role, employees may also be eligible for additional compensation and benefits, including but not limited to incentive programs, commissions, equity grants, health and wellness benefits, retirement contributions, and paid time off.

The estimated pay ranges for this role are as follows:

• Based in British Columbia: CAD 145,840.00 - CAD 182,300.00 
• Target Bonus Percentage 15%

The successful candidate’s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location.

See yourself at Twilio

Join the team as Twilio’s next Sr. Analyst, Strategic Measurement.

About the job

We are actively recruiting for this role to fill an existing vacancy. This position is needed to serve as the "New Frontiers" lead for the Marketing Strategy, Analytics & Innovation team, focusing on ambiguous, highly strategic emerging channels, potential programs & measurement optimization/instrumentation. You will be responsible for defining, measuring, and accelerating our growth in new digital landscapes, specifically focusing on AI Engine Optimization (AEO), brand measurement and advanced attribution frameworks. Partnering closely with the global marketing analytics teams, Brand, Demand Gen, PR, Content, and Developer Network teams, you will execute against high-visibility objectives enabling marketing's business impact to executive leadership. Ideally, this position has a strong statistical background, a substantial capacity for hypothesis-driven thinking, and the ability to deliver "unmistakable clarity" in complex executive presentations.

Responsibilities

In this role, you’ll:

• Analyze LLM visibility and Share of Voice, create a continuous feedback loop across various teams to optimize Twilio's presence in AI search/AEO (answer engine optimization), drive enablement and operational efforts to ensure consistent tool usage and storyline.
• Support the strategy, data ingestion, and modeling required to build and maintain net new and existing brand measurement components. Drive a single, cohesive narrative combining disparate data sets.
• Inspire experimentation adoption in teams. Build the frameworks and structure to drive experimentation rigor and clarity of incrementally of marketing initiatives.
• Support Media Mix Modeling (MMM) and Multi-Touch Attribution (MTA) initiatives to understand the impact of various marketing channels on Sign Ups, SQLs, activations, and guide budget allocation.
• Translate complex data sets into actionable insights and strategic recommendations for exec-level audiences.
• Own enablement efforts for emerging channels, sharing accomplishments, KPIs, and cross-team collaborations broadly across the marketing organization.

Qualifications 

Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table!

*Required:

• 5+ years of experience in statistical analysis, experimentation and/or scenario planning.
• A strong understanding of SEO and emerging AI Search (AEO/GEO) landscapes.
• A hypothesis-driven thinker who does not just report the "what," but actively tests the "why". Able to formulate testable guesses and distill the essential from complex marketing data.
• Experience with running or interpreting advanced measurement frameworks (Incrementality, MMM, MTA).
• Highly reliable and a self-starter.
• Interest or experience in applying AI-driven solutions to analytics workflows.
• Strong communication skills with the ability to communicate effectively with both technical and non-technical audiences
• Detail-oriented with a passion for clean, trustworthy data.
• Strong analytical skills. 
• Excellent collaborator across cross functional teams; skilled in managing stakeholder projects end to end.

Desired:

• Experience supporting various stakeholder functions and their insights: Brand, PR, Social, Content, Demand Generation
• Experience with BI tools (Tableau, Looker Studio) and modeling (ROI, LTV:CAC, payback).
• Interest or exposure to fraud monitoring tools and processes.
• Working knowledge of Customer Data Platforms (CDPs) and analytics data integrations.

Location

This role will be remote, and based in Alberta, British Columbia, or Ontario, Canada.

Travel 

We prioritize connection and opportunities to build relationships with our customers and each other. For this role, approximately 15% travel is anticipated to help you connect in-person in a meaningful way. 

What We Offer

Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location. Based on role, employees may also be eligible for additional compensation and benefits, including but not limited to incentive programs, commissions, equity grants, health and wellness benefits, retirement contributions, and paid time off.

The estimated pay ranges for this role are as follows:

• $90,800 - $113,500 CAD
• Target Bonus Percentage 12.50%

The successful candidate’s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location. 

Overview:

Precisely is seeking an Associate Technical Account Manager to lead strategic and technical engagements with our North American customers. Precisely Technical Account Managers are trusted advisors who own business critical support and expansion programs with our most strategic customers. Technical Account Managers work cross functionally to enable both technical and non-technical teams to improve efficiency, expedite fixes, improve visibility for stakeholders, streamline communications, and reduce risks to our customers’ success. Our Technical Account Managers delight customers through collaborative escalation prevention, leadership on best practice adoption, and coordinating ongoing change management efforts. ​ 

What you will do:

• Manage assigned enterprise accounts across North America.​
• ​​Program management: Strategic guidance and tracking of customer goals, product updates, support issues, and development tasks.
• ​​Escalation ownership: Driving resolution of high-profile issues, coordination of technical fix deployment and testing, delivery of root cause analysis documentation, and assessing/addressing risks.​
• ​​Shepherding customer implementations through each phase of the project lifecycle from ideation through to post launch support and continuous improvement.​
• ​​Executive presence in managing customer stakeholders, internal coordination, and influencing decision makers at all levels.​
• ​​Coordination and communication with all parties involved in customer projects, renewals, and expansion opportunities.​

What we are looking for:

Required Qualifications:  

• Relevant degree or equivalent work experience 
• Exceptional verbal/written communication and organizational skills 
• Experience managing complex customer solutions in a production environment 
• Ability to liaise cross functionally with internal and external technical and non-technical teams 
• Confident in leading discussions with customers to drive resolution and alignment toward proactive and preventive improvements to processes and mechanisms 
• Working knowledge of leading project management methodologies 
• Technical aptitude for both emerging technologies and legacy support models 
• Experience working with public cloud providers and/or on-premises software hosting 
• 2 years experience in a customer facing role in technical support, program management, project management, sales engineering, or technical account management  

AI Skills/Knowledge:

• Use AI to surface at-risk accounts and usage signals; drafts QBR narratives and data analysis with AI assistance; experience with AI-powered support deflection or escalation routing; synthesizes product feedback at scale using AI summarization
• Identifies and automates repetitive workflows using AI tools; uses AI to synthesize cross-functional data and generate executive-ready reporting; experience with AI-driven process mapping or bottleneck analysis; comfort building or managing AI-assisted workflows without deep technical background

Preferred Skills:

• Experience with AI-assisted coding tools (e.g., GitHub Copilot, Cursor); uses AI for code review, documentation, and test generation; familiarity with LLM APIs or agentic workflows; understands responsible AI principles including bias, security, and explainability
• Prior experience managing customer support workflows or operations 
• Working knowledge of one or more Precisely product domain 
• Technical knowledge of SQL, RESTful services, ETL, and MDM solutions
• Ability to travel domestic and international up to 10% of the year 

#LI-DR1

#LI-Remote

Location: This position is remote within the United States or Canada. 

Role Summary: 

Censys is seeking a Senior Backend Engineer to join our Exposure Management team. Our Exposure Management solution is a growth product for Censys and depends on a world-class backend architecture to deliver real-time, high-fidelity visibility to our customers. We’re looking for an engineer who can design, build, and extend large-scale, real-time backend services that leverage Censys’ massive datasets to power internal product APIs and external customer-facing applications.

This role requires someone who is comfortable owning backend services end-to-end, integrating data from multiple internal systems, and operating in production environments where reliability, observability, and correctness matter. As with all roles at Censys, we expect a strong customer focus, a collaborative mindset, and a desire to continuously learn and improve both our systems and our team.

What You’ll Do:

• Design, build, and own backend APIs and gRPC services that integrate data from multiple internal teams and systems in a clean, well-architected manner
• Build and evolve real-time and near–real-time backend services and data pipelines that power Exposure Management and Attack Surface Management products
• Leverage AI and LLMs to enhance automation, accelerate development workflows, and improve customer-facing intelligence
• Partner closely with Product and other Engineering teams to prioritize features, influence the Exposure Management roadmap, and deliver customer value on tight timelines
• Provide technical leadership through design reviews, mentorship, and setting a high bar for code quality, performance, and operational reliability
• Design and maintain automated CI/CD workflows, including testing, monitoring, alerting, and deployment, to ensure services are production-ready and observable

What You’ll Bring: 

• A positive attitude biased towards action and iterative problem solving, learning as we grow every step of the way.

• 5+ years of experience in software engineering.
• 3+ years of experience with Golang.
• Experience designing and consuming REST and gRPC APIs in service-oriented or microservice architectures
• Strong distributed systems fundamentals, including experience building horizontally scalable, fault-tolerant systems
• The ability to thoughtfully participate in technical discussions and drive towards data-driven decisions amidst ambiguity and competing priorities.
• Strong communication and documentation skills. Explaining complex technical concepts to other engineers, designers, salespeople, and content marketers is no problem for you.

What Sets You Apart:

• Strong interest in harnessing AI and LLM tools as a force multiplier - using it to code smarter, iterate faster boosting productivity and enhancing product capabilities
• You have experience with microservice-based designs with GCP PubSub, etc, and know their tradeoffs.
• Experience building, deploying, and maintaining containerized services in a Kubernetes based environment.
• You understand the value of building maintainable software. Some of your first tasks when building a new service are ensuring test coverage enforced by CI, adding linters, and adding code complexity checks. You enjoy a good abstraction, and promote established design patterns, but also know when to think outside the box.
• A deep understanding of how the Internet works. For example, WHOIS, Certificate Subject Alternative Names (SANs), and DNS record types should not be foreign to you.

For high cost of living areas (San Francisco Bay, New York City, and Seattle), the expected salary range for this position is $157,000 USD - $188,000, plus bonus eligibility and equity. 

For other US locations, the expected salary range for this position is $137,000 USD - $175,000 USD, plus bonus eligibility and equity.  

Job level and actual compensation will be decided based on factors including, but not limited to, individual qualifications objectively assessed during the interview process (including skills and prior relevant experience, potential impact, and scope of role), market demands, and specific work location. The listed range is a guideline, and the range for this role may be modified. For roles that are available to be filled remotely, the pay range is localized according to employee work location by a factor of between 83% and 100% of range. Please discuss your specific work location with your recruiter for more information.

Censys offers a competitive benefits package to employees, including equity, health, dental & vision coverage, retirement with company contribution, parental leave, mental health & wellness benefits, flexible PTO, and a professional development stipend. Censys also offers sales incentive pay for most sales roles and an annual bonus plan for eligible non-sales roles. Censys’s compensation and benefits are subject to change and may be modified in the future. Please see our careers page for more details.

We will work to ensure individuals with disabilities are provided reasonable accommodation to apply for a role, participate in the interview process, perform essential job functions, and receive other benefits and privileges of employment. If you require accommodation, please reach out to your recruiter. These modifications enable an individual with a disability to have an equal opportunity not only to get a job, but successfully perform their job tasks to the same extent as people without disabilities.

To ensure the integrity of our hiring process and facilitate a more personal connection, we require all candidates to keep their cameras on during video interviews. Additionally, if hired, we would love to bring you to our HQ in Ann Arbor for in-person onboarding.

By applying for this job, the candidate acknowledges and agrees that any personal data contained in their application or supporting materials will be processed in accordance with our Censys Privacy Policy.

Our roots are in Ann Arbor, Michigan and our innovation is fueled by the team’s global perspectives. For this role, we are open to remote employees across the continental US. We value diversity and are committed to creating an inclusive environment for all employees. Censys is an equal opportunity employer.

Note to external recruiters/agencies: We are not currently engaging with third-party agencies for this role and will not accept unsolicited outreach. We kindly ask that you do not submit resumes or candidate profiles to our team.

Staff Product Manager, AI PlatformThe Opportunity: Define the Future of Agentic AI in the Enterprise

Invoca is an AI-powered revenue execution platform that brings together marketing, commerce, and contact center teams to turn every customer interaction into measurable, profitable growth. Join our dynamic, fast-growing team, where innovation and collaboration are at the core of our culture.

By revealing intent across voice, SMS, and digital channels, Invoca helps enterprises drive better customer experiences, increase revenue, and operate with confidence at scale.

We are a fast-growing company defined by a strong product culture, deep technical ambition, and a commitment to building AI systems that are reliable, transparent, and outcome-driven. Join us to build the core intelligence layer for one of the most innovative enterprise platforms in the market.Build the Foundation for Agentic AI at Scale

Invoca is building a shared AI Platform that powers every AI-driven product and every agentic experience we continue to deliver. This foundational platform is the execution layer behind Voice AI, SMS Agents, Signals, Scoring, and emerging copilots.

This is a rare and critical opportunity to define how agentic AI actually runs in production inside an enterprise SaaS company. You will own the execution layer—from orchestration and context to governance, evaluation, and developer experience. Your work will determine not just what Invoca’s AI can do, but how safely, consistently, and efficiently it does it at scale.The AI Platform Team

The AI Platform team builds the shared systems that empower product teams across Invoca to ship AI-powered experiences with confidence. We operate at the intersection of infrastructure, applied AI, and product design, focusing on:

• Agent execution and orchestration
• Context management and grounding
• Evaluation, observability, and quality control
• Governance, safety, and multi-tenant isolation
• Developer and product experiences that scale across teams

Our success is measured by the leverage we create: how many teams can build on the platform, how safely they can innovate, and how quickly high-quality AI experiences reach customers.Your Role and Impact

As a Staff Product Manager, AI Platform, you will own the product vision and roadmap for Invoca’s agentic AI platform—the foundational layer that runs, governs, and evolves AI agents across channels and products.

This role requires deep technical judgment and a strong systems mindset. You will focus on the architectural and experience boundaries of the platform, not just a single AI feature or agent.

You will operate as a senior individual contributor reporting to the VP of Product, with broad influence across engineering, data, security, and product teams. Success requires strong systems thinking, platform judgment, and the ability to balance cutting-edge innovation with enterprise-grade trust.What You'll Be Doing (Key Responsibilities)

• Drive Strategy: Own the end-to-end product strategy and roadmap for Invoca’s AI Platform, aligning technical foundations with company-level AI principles around reliability, safety, and measurable outcomes.
• Define Execution: Establish how AI agents execute in production, including orchestration patterns, tool invocation semantics, context handling, and behavior across asynchronous and real-time environments.
• Architect Contracts: Establish clear, durable platform contracts—APIs, configuration schemas, versioned artifacts—that make agent behavior portable, governable, and scalable across products and channels.
• Partner for Scale: Collaborate deeply with AI engineering and data teams to translate agentic patterns into reliable systems, making principled tradeoffs across reasoning quality, latency, cost, and operational complexity.
• Enable Adoption: Drive standardization through paved roads, golden paths, SDKs, and shared components that reduce bespoke implementations and accelerate internal adoption.
• Enforce Quality: Define and enforce platform-level quality, safety, and governance mechanisms, including evaluation workflows, promotion gates, observability, Role-Based Access Control (RBAC), and auditability.
• Shape Experience: Shape the developer and product experience for building, testing, debugging, and operating AI agents, ensuring the platform is intuitive, debuggable, and trusted by internal teams.
• Guide Evolution: Guide the evolution from an internal platform to a product-grade system, informing customer-facing configuration and studio experiences without compromising guardrails, privacy, or reliability.
• Make Build/Buy Decisions: Evaluate build vs. buy decisions for foundational AI infrastructure and guide vendor integrations behind stable, well-defined platform contracts.
• Measure Success: Define success metrics for the AI Platform and continuously measure impact through adoption, reuse, quality, performance, and cost efficiency.
• Stay Current: Stay current on advancements in agentic AI, orchestration frameworks, and evaluation best practices, translating signal into pragmatic product decisions rather than chasing hype.

What You'll Bring (Core Qualifications)

• Experience: 8+ years of product management experience, with meaningful time spent building platforms, infrastructure, or developer-facing products used by other teams.
• Technical Foundation: Background in engineering, computer science, or equivalent hands-on experience building and operating complex software systems.
• System Knowledge: Strong systems-level understanding of AI-powered and distributed systems, including LLM-based agents, multi-step workflows, retrieval, and tool calling—sufficient to reason about execution models and failure modes without writing production code.
• Contract Definition: Demonstrated experience defining and scaling platform contracts, including APIs, configuration models, versioning strategies, and lifecycle management.
• Governance & Standards: Proven ability to introduce standards, governance, and quality controls in ways that accelerate product velocity rather than constrain it.
• Quality Focus: Deep appreciation for evaluation, observability, and regression testing as first-class requirements for AI systems.
• Enterprise Awareness: Experience operating in enterprise, multi-tenant environments where privacy, security, compliance, and auditability are core design constraints.
• Developer Empathy: Strong instincts for developer experience, including the use of golden paths, tooling, and defaults to drive adoption and reduce fragmentation.
• Tradeoff Mastery: Track record of making hard tradeoffs across latency, cost, quality, and reliability in complex, distributed systems.
• Influence: Exceptional communication and influence skills, with the ability to align engineering, data science, product, and Go-To-Market (GTM) stakeholders around shared platform goals.

Desirable, But Not Required

• Experience with agentic AI frameworks (e.g., LangChain, LangGraph, ReAct-style systems) or standardized tool invocation models (e.g., MCP).
• Familiarity with real-time systems such as voice, streaming, or low-latency inference.
• Background in enterprise SaaS or compliance-heavy domains.

Location & Inclusion

• Location: This role is remote and open to candidates located in the United States and Canada only. While visa sponsorship is not available, transfers will be considered.
• Diversity, Equity & Inclusion: Invoca is committed to building an inclusive culture that values diverse perspectives and experiences. We are proud to be an equal opportunity employer and do not discriminate based on race, color, ancestry, religion, gender identity, sexual orientation, age, or disability.

Salary, Benefits & Perks:

At Invoca, all new hires in the U.S. receive benefits starting on day one of employment. Our benefits offerings include:

Please note that benefits for teammates outside the U.S. may vary in accordance with their country’s laws and regulations.

• Flexible Time Off – We encourage a healthy work-life balance. Our flexible paid time off policy allows you to recharge and take time away as needed.
• Paid Holidays – Invoca provides 16 U.S. paid holidays, including a winter break, giving you ample opportunity to refresh and spend time with friends and family.
• Health Benefits – Our healthcare program includes medical, dental, and vision coverage, with multiple plan options so you can choose what works best for you and your family. Fertility assistance is also included.
• Retirement – Invoca offers a 401(k) plan through Fidelity with a company match of up to 4%.
• Stock Options – All employees are invited to share in Invoca’s success through stock options.
• Mental Health Program– Well-being support on a broad range of issues is available through our SpringHealth program.
• Paid Family Leave – Up to 12 weeks of 100% paid leave is provided for baby bonding, adoption, and caring for family members.
• Paid Medical Leave – Up to 12 weeks of 100% paid leave is provided for childbirth and medical needs.
• InVacation – As a thank-you to our long-term team members, we offer a bonus after 7 years of service.
• Wellness Subsidy – We provide a subsidy that can be applied toward gym memberships, fitness classes, and more.
• Position Base Range - Salary Range $140,000-$208,000 / plus bonus potential

DEI Statement

We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity workplace.

About Life360

Life360’s mission is to keep people close to the ones they love. Our category-leading mobile app,Tile tracking devices, and Pet GPS tracker empower members to protect the people, pets, and things they care about most with a range of services, including location sharing, safe driver reports, and crash detection with emergency dispatch. Life360 serves approximately 95.8 million monthly active users (MAU), as of December 31, 2025, across more than 180 countries.

Life360 delivers peace of mind and enhances everyday family life with seamless coordination for all the moments that matter, big and small. By continuing to innovate and deliver for our customers, we have become a household name and the must-have mobile-based membership for families (and those friends who are basically family).

Life360 has more than 500 (and growing!) remote-first employees. For more information, please visit life360.com.

Life360 is a Remote First company, which means a remote work environment will be the primary experience for all employees. All positions, unless otherwise specified, can be performed remotely (within the US and Canada) regardless of any specified location above. 

We are AI Native

We are building an AI native company where AI is an integral part of how we build and operate. AI tool usage during interviews varies by role. You may be asked to demonstrate proficiency with AI tools, discuss how you leverage AI, or complete interview exercises without AI assistance. Your Recruiter will provide clear guidance as you move through the interview process.

Undisclosed use of AI not previously discussed with or approved by your Recruiter may impact your candidacy.

About The Team

The AI Lab is a small, founder-led team operating like a zero-to-one startup inside Life360, building the company’s next chapter. Our mission is to transform Life360 from the app you open to find your family into an intelligent operating system families rely on daily. We design and build an AI-powered layer on top of our family graph, leveraging our core location technologies and global 100 million-user base to proactively surface what matters across location, schedules, and everyday life.

About the Job

Your role is owning how Life360's deterministic backend (location data, the family graph, behavioral signals, user insights) pairs with the probabilistic world of LLMs. You decide how those two sides talk to each other, and you make sure the seams don't show.

You own the inference pipeline end to end: model selection, serving infrastructure, evaluation loops, prompt and context strategy, and the cloud services that keep it all running in production. You make the tradeoffs between latency, cost, and quality. You build the eval harness that tells us whether the system is actually getting better, not just feeling different. If you do this job right, the product feels seamless to users, the data stays safe, and inference costs don't run away from us. You are a cloud engineer who is deeply fluent in how AI systems actually work in production. 

For candidates based in the US, the salary range for this position is $190,000 to $280,000 USD. For candidates based out of Canada, the salary range for this position is $220,000 to $260,000 CAD. Note: Please be aware that the job title for positions in Canada will be "Developer" in lieu of "Engineer." We take into consideration an individual's background and experience in determining final salary - therefore, base pay offered may vary considerably depending on geographic location, job-related knowledge, skills, and experience. The compensation package includes a wide range of medical, dental, vision, financial, and other benefits, as well as equity.

What You’ll Do

• Architect the inference pipeline that turns Life360 into a context layer LLMs can reason over: soul files, family context, behavioral signals, document understanding.
• Choose models. Choose hosting. Decide what is self-hosted, API-based, fine-tuned, or prompt-engineered. Revisit those decisions as the landscape changes.
• Build the serving infrastructure. Latency budgets, batching, caching, fallbacks, graceful degradation. Make it run at scale before scale gets here.
• Build the eval loop. Know whether changes make the product better or worse, not just whether the demo works. This is the difference between a real product and a magic trick.
• Own the cost model. Track spend per user, per feature, per family. Find the levers (context compression, model routing, pre-computation) that keep unit economics working from a test group to millions.
• Define what gets persisted, what gets summarized, and what gets thrown away. The architecture decision of "what does our data look like to an LLM" lives with you.
• Set the bar for safety, privacy, and trust at the infrastructure layer. Sensitive categories filtered before they propagate. Encryption, access controls, audit trails built in, not bolted on.

What We’re Looking For

If there's one trait we need above all others, it's self-starter energy. As we've gotten bigger, we've been more open to roles with clearly defined schedules and processes. That doesn't work in a startup. We need people on founder hours, not office hours — with a huge desire to win. You'll be a cofounder of this initiative.

• You operate without a spec. You'd rather have a conversation, a sketch, and 24 hours than a 30-page PRD and a week.
• You ship every day. Not "make progress." Ship. Even rough. Even ugly. Momentum matters more than polish at this stage.
• You push for more. You won't wait to be told what to do. You demand excellence of yourself and the people around you.
• You hold strong opinions and change them when the evidence moves. You push back. You concede fast when wrong.
• You're a customer of what we build. Try it if you haven't.

The bar

• Deep engineering experience, with significant time spent building and running AI systems in production at meaningful scale. Real users, real load, real on-call.
• Fluent in modern LLM serving (vLLM, TGI, SGLang, hosted APIs — whatever's right for the job). No religion about it.
• You think in evals. You've built harnesses. You know the difference between vibes-based iteration and real progress because you've felt the pain of not having one.
• You can build a cloud system from the ground up. Pick the services, wire them together, make them reliable, keep the bill in check.
• Strong opinions about cost. You've seen inference bills run out of control and have instincts for where the leaks come from.
• AI-native in your daily workflow. Hands-on with Claude Code, Cursor, or equivalent. You think natively in agentic workflows, prompt engineering, context window management, MCP / function calling.
• Comfortable deciding with incomplete information. The spec will be a moving target. You don't need it to settle before you start building.
• Strong written communication. You write specs, decision records, and playbooks that an agent (and a human) can act on precisely.
• Experience with agent systems, retrieval pipelines, or long-context personalization.
• Privacy architecture experience in multi-user systems where context is shared across people with different rights to see it.
• You've built something where the data itself was the moat — and you understand why that's different from building on public data.

Our Benefits

• Competitive pay and benefits.
• Medical, dental, vision, life and disability insurance plans (100% paid for US employees). We offer supplemental plans for medical and dental for Canadian employees.
• 401(k) plan with company matching program in the US and RRSP with DPSP plan for Canadian employees.
• Employee Assistance Program (EAP) for mental wellness.
• Flexible PTO and 12 company wide days off throughout the year.
• Learning & Development programs.
• Equipment, tools, and reimbursement support for a productive remote environment.
• Free Life360 Platinum Membership for your preferred circle.

Life360 Values

Our company’s mission driven culture is guided by our shared values to create a trusted work environment where you can bring your authentic self to work and make a positive difference 

• Be a Good Person - We have a team of high integrity people you can trust. 
• Be Direct With Respect - We communicate directly, even when it’s hard.
• Members Before Metrics - We focus on building an exceptional experience for families. 
• High Intensity High Impact - We do whatever it takes to get the job done. 

Our Commitment to Diversity

We are an equal opportunity employer and value diversity at Life360. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status or any legally protected status.  

We encourage people of all backgrounds to apply. We believe that a diversity of perspectives and experiences create a foundation for the best ideas. Come join us in building something meaningful. Even if you don’t meet 100% of the below qualifications, you should still seriously consider applying!

#LI-Remote

____________________________________________________________________________

Overview:

We are building the next generation of our SaaS platform, and we need someone to own the quality architecture that makes it all trustworthy. As a Principal Technology Architect - QA, you will design the systems, standards, and governance that raise the bar for quality across every product segment we ship.

We are an AI-first organization. You will put that into practice by bringing AI-driven testing, intelligent automation, and modern quality tooling into the way our teams work every day. This is a hands-on architecture role, not a policy desk. You will build test frameworks, design quality gates, set reliability targets, and create the shared infrastructure that teams actually adopt because it makes their lives easier.  You will work closely with engineering leadership to connect quality strategy to business outcomes. When you recommend a change, people across the org will listen, because your technical credibility and track record back it up.  You will also mentor engineers, shape how we hire for quality mindset, and help grow the next generation of technical leaders on our teams.  If you get excited about solving hard problems at scale, rethinking how quality works in a modern SaaS org, and leaving things better than you found them, we would love to talk.

What you will do:

• Set the quality architecture direction for the org: design quality gates, define reliability targets, and choose the testing infrastructure that all product segments build on.
• Build and maintain a governance model for quality practices so that standards, processes, and tooling are adopted consistently across engineering teams.
• Design and deliver scalable test automation frameworks that teams can adopt and extend to improve coverage, speed, and confidence in every release.
• Bring AI into quality engineering: evaluate and roll out AI-driven test generation, intelligent test selection, defect prediction, and automated monitoring.
• Own the performance and resilience strategy: set performance budgets, define monitoring standards, and create disaster recovery and incident response frameworks.
• Partner with product and engineering leaders to balance release velocity with system health, making sure teams can ship fast without cutting corners on quality.
• Evaluate and introduce new tools, patterns, and practices that keep our quality approach current as the platform and industry evolve.
• Mentor engineers across teams, raise the bar on how we hire for quality mindset, and contribute to engineering maturity across the organization.
• Represent Precisely externally as a thought leader in quality engineering through talks, writing, or industry engagement.

What we are looking for:

Required:

• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. Equivalent work experience is accepted in place of a degree. An advanced degree is a plus.
• Experience: 15+ years of progressive experience in software quality engineering, test architecture, or related technical leadership roles, with demonstrated org-wide architecture leadership
• Quality architecture: Deep expertise in test automation frameworks, CI/CD pipeline design, quality gate implementation, and testing strategies for large-scale SaaS platforms.
• AI: Hands-on experience applying AI to quality workflows (e.g. AI-driven test generation, intelligent test selection, or automated defect detection)
• Leadership: Track record of driving adoption of technical standards across multiple teams or product areas, including working with leaders who do not report to you
• Travel is required: Yes – Approximately 10%

AI Skills/Knowledge:

• Comfortable using generative AI tools (e.g. GitHub Copilot, Claude Code, or custom LLM integrations) to accelerate day-to-day quality workflows such as test generation, defect triage, and root-cause analysis.
• Able to critically evaluate AI-generated outputs and set guardrails so that AI-produced test artifacts meet reliability, security, and compliance standards.
• Experience evaluating and integrating AI-powered quality tools (e.g. autonomous testing platforms, AI-based test maintenance, predictive analytics for defect detection) into org-wide workflows.
• Open to continuously adopting new AI capabilities as they emerge and excited to shape how the org integrates them into quality practices.

Preferred Skills:

• Experience defining and scaling quality practices across multiple product segments in a large SaaS or cloud-native organization.
• Familiarity with contract testing, chaos engineering, or advanced reliability practices (SLOs/SLIs, error budgets).
• Bonus points for experience establishing quality centers of excellence or community-of-practice models across engineering organizations.
• Exposure to security testing practices, compliance frameworks, or regulated industry quality standards.
• Experience with observability and monitoring platforms (Datadog, Splunk, Grafana, PagerDuty) at an architectural level.
• Track record of representing an organization externally through conference talks, published writing, or industry working groups in quality engineering.

#LI-SR1

About the team + role

We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards.

The People Systems team builds and operates the technology that supports Robinhood’s employees across their entire lifecycle. The team focuses on Workday and connected systems, ensuring reliable operations, strong data quality, and scalable solutions for a growing global workforce. You will work closely with partners across HR, Engineering, Finance, and Legal to deliver systems that support hiring, onboarding, payroll, and compliance.

As a People Systems Manager, you will lead the design, development, and operation of Robinhood’s People Systems ecosystem with Workday as the foundation. You will contribute directly to system configuration, integrations, and architecture while guiding a team of engineers and analysts. This role also focuses on applying AI tools and automation to reduce manual processes, improve data accuracy, and enhance employee support. You will help define how AI is applied within People Systems to improve efficiency and scalability!

This role is based in our Menlo Park, CA office, with in-person attendance expected 5 days per week.

At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office experience is intentional, energizing, and designed to fully support high-performing teams.

What you’ll do

• Own and evolve Robinhood's core People Systems with Workday as the foundation — driving configuration, integrations, Extend development, and architectural decisions.
• Lead as a hands-on technical manager: you write, review, and ship alongside your team rather than delegating from a distance.
• Actively use AI-assisted development tools (e.g. Cursor, Claude Code, GitHub Copilot) to accelerate delivery — and set the standard for AI-augmented workflows on your team.
• Design and build AI-powered automations and agents that reduce manual HR operations, improve data quality, and enhance the employee experience.
• Build and maintain integrations across the People tech stack — deep ownership of EIB-based integrations required, Workday Studio experience strongly preferred.
• Prototype and productionize AI capabilities embedded in HR workflows (e.g. intelligent routing, document processing, conversational HR interfaces).
• Drive major initiatives including vendor and worker management systems, Workday enhancements, and Workday Extend investments.
• Support international growth and M&A by enabling scalable People systems for new geographies.
• Establish a long-term People Systems roadmap that is AI-first — not AI-curious — balancing near-term operational needs with a bold future-state architecture.
• Maintain a high bar for data quality, security, privacy, and compliance across all People systems.
• Lead and grow a distributed team of FTEs and contractors, building strong technical ownership and accountability.

What you bring

• 7+ years of progressive People Systems or HRIS experience, including 2+ years managing technical teams.
• 4+ years of hands-on Workday experience with strong technical depth across Core HCM, integrations, and Extend.
• Demonstrated use of AI coding tools such as Cursor, Claude Code, or GitHub Copilot — we'll ask you to walk us through projects where these tools changed how you work.
• Proven experience building AI agents, automations, or LLM-powered workflows — side projects, internal tools, and production systems all count.
• Deep experience building and supporting Workday integrations; EIB required, Workday Studio strongly preferred.
• Familiarity with Greenhouse and/or Ashby.
• Strong cross-functional partnership skills across HR, Engineering, Finance, and Legal.
• Ability to operate in fast-paced, ambiguous environments — you make decisions with incomplete information and iterate quickly.
• A portfolio or track record of shipped AI projects: describe what you built, what tools you used, and what impact it had.
• Strong analytical and problem-solving skills with a bias toward action and measurable outcomes.

Leadership expectations

Our ambitious roadmap requires a great culture shaped by exceptional leaders. Here’s what we expect from them:

• Drive high performance by setting clear, focused goals, giving real-time feedback, stretching top talent, and scaling impact through focus, innovation, and tech.
• Hire and retain top talent by setting a high bar, hiring only those who raise it, investing in onboarding, and addressing talent issues quickly and fairly.
• Create community by connecting work to purpose, removing friction while prioritizing safety, building trust and inclusion, and leading from the front with integrity.

What we offer

• Challenging, high-impact work to grow your career.
• Performance-driven compensation with multipliers for outsized impact, bonus programs, equity ownership, and 401(k) matching.
• Best-in-class benefits to fuel your work, including 100% paid health insurance for employees with 90% coverage for dependents.
• Lifestyle wallet — a highly flexible benefits spending account for wellness, learning, and more.
• Employer-paid life & disability insurance, fertility benefits, and mental health benefits.
• Time off to recharge including company holidays, paid time off, sick time, parental leave, and more!
• Exceptional office experience with catered meals, events, and comfortable workspaces.

Value Engineering Lead at Unframe 

Location: United States (Remote)

About Unframe

Unframe is an AI-first startup helping the world’s largest enterprises bring LLM-powered applications to life in days - not months. We combine the speed of a product company with the flexibility of a consultancy, helping customers move from idea to deployed AI systems faster than anyone else in the market.

Backed by Bessemer, Craft, and TLV Partners with $50M in Series A funding, we’re building a fast-growing, revenue-generating company working with Fortune 500 customers globally

About the role:

We’re hiring our first Value Engineering Lead to define and scale how Unframe:

1. Identifies the right use cases
2. Quantifies and proves business value
3. Converts POCs into enterprise programs

You will operate at the intersection of sales, product, and strategy, helping shape deals, train teams, and build the systems that turn value into a repeatable growth engine.

What You’ll Do

• Partner with AEs early in deals to identify and refine the highest-impact use cases
• Guide conversations from “what do you want to build” → where is the measurable value
• Apply structured frameworks to prioritize use cases based on:
• volume, cost, and frequency
• operational friction
• business impact

• Develop simple, repeatable frameworks (not heavy training decks), such as:
  • value discovery questions
  • use case qualification criteria
  • “good vs bad” use case patterns

What we are looking for:

• 5–10+ years in Value Engineering / Value Consulting
• Strong ability to connect technical solutions to business outcomes
• Comfortable working in ambiguity and shaping problems from scratch
• Excellent at structuring and simplifying complex ideas

Why join us?

• Real ownership from day one. Drive decisions, shape ideas and make them work.
• Your fastest learning years. Build alongside founders and VPs in a space that moves weekly.
• You'll have the opportunity to write and build what comes next.

Ready to Build the Future?

If this opportunity excites you, apply now!

We are seeking a Senior Machine Learning Engineer to join the Growth Tech Alliance. In this role, you will architect and deploy the robust infrastructure behind our intelligent marketing systems. You will be responsible for maturing algorithmic prototypes into high-performance production systems, ensuring our AI-driven marketing optimization is served reliably and autonomously at a global scale.

S'more about the team

We are hiring a Senior Machine Learning Engineer to take our AI tooling to the next level by architecting and deploying the robust infrastructure behind our intelligent marketing optimization systems. You will provide critical engineering execution for our AI initiatives. You will develop scalable microservices for predictive scoring, orchestrate complex LLM-based agents for creative intelligence. As the ML engineering expert for the team, you will drive the maturation of algorithmic prototypes into high-performance production systems with maximum Speed & Agility, shaping the future of how HelloFresh automates marketing at an unprecedented scale.

Lettuce share what this role will be responsible for

As a core member of the engineering team, you will focus on productionizing ML infrastructure across several domains:

• Build robust integration layers for visual AI pipelines that process multi-modal embeddings that power various predictive models.
• Transition proof-of-concept models into resilient production microservices and architect LLM-based orchestration frameworks.
• Engineer high-throughput, low-latency data pipelines to process 1P data and pipeline signals into external platforms like Meta and Google.
• Collaborate with data scientists and other engineers in a cross-functional team to improve HelloFresh’s value forecasting efficiency.
• Establish CI/CD processes, feature stores, and drift detection to ensure continuous delivery and model reliability.
• All other duties, as assigned

Sound a-peeling? Here's what we're looking for

• Experience leading the end-to-end lifecycle of production ML systems, from architectural design to scalable deployment and monitoring.
• Expertise in leveraging hyperscaler ecosystems (AWS, GCP, Azure) to build cost-effective, resilient, and automated ML infrastructure.
• Deep technical proficiency with modern ML frameworks (PyTorch, TensorFlow, HuggingFace)
• Expert programming skills in Python and PySpark.
• A BS/MS in Computer Science or a related engineering field, coupled with a proven track record of bringing ML systems from prototype to high-traffic production.
• Proven experience engineering robust data architectures that reliably process and combine diverse data formats, ranging from structured offline conversion data to unstructured multimedia assets.
• A demonstrated bias for action and extreme ownership, eager to adopt Gen AI tools to creatively solve architectural challenges and enhance engineering velocity.

Let’s cut to the cheese, this is why you'll love it here

• Box Discount - Amazing discounts on 1 box per week! 75% discount on weekly HelloFresh and Chefs Plate meal kits AND 50% off weekly Factor meal box.
• Health & Wellness - Health & Dental benefits from day 1, a Health Spending Account, unlimited access to the Headspace app to meet your self-care needs, and 25% discount on GoodLife fitness memberships!
• Vacation & PTO - Time off is also an important part of self-care! We offer generous vacation and PTO to help you create a good work-life balance. 
• Family Benefits - A parental leave top-up program for expectant parents.
• Growth & Development - We support your career progression and invest in your continued learning through experiences and initiatives owned by our dedicated L&D team
• Work Hard & Have Fun - From team socials to engaging company days, you’ll have plenty of opportunity to experience the fun!
• Diversity & Inclusion Initiatives - With impactful ERG’s like FreshPride, Women Empowered and LIMES, we are committed to our diversity, equity & inclusion efforts.
• Food Puns - this one is kind of a big dill if you haven’t already noticed. We even have some punny meeting room names!

Flexible Hybrid Approach

At HelloFresh, we know that flexible work arrangements are essential in enabling you to do your best work, while balancing your personal and life needs. Offering remote work flexibility, along with the opportunity to interact and collaborate in the office are all a part of creating a great employee experience. 

To meet these needs, we are pleased to provide Flexible Hybrid work. Flexible Hybrid is a people-first approach that is based on choice, trust, personalization, and empowers teams to choose when and how often they work from the office and work from home, in addition to team days and company days. This means a minimum of 2 days in office per week, with most teams in office between 2-3 days a week.

#LI-HYBRID

#Engineering

HelloFresh Canada uses AI-integrated technology to help us process and evaluate applications more efficiently. This includes tools that screen and assess candidate qualifications based on the requirements for this role. While these tools assist our workflow, all final selection decisions are made by our hiring team.

This is a posting for an existing vacancy. We are actively seeking to fill this position.

S'more about the team

As a Staff Analytics Engineer, you will be the technical architect and strategic lead for data assets driving HelloFresh’s growth globally. Data-driven decision making is at the core of our company culture and your extensive experience and knowledge across technical and business related topics will enable us to make better and faster decisions. You will work with teams across the Growth Alliance - for example Conversions, Payments, Pricing/Benefits, Communications and Adtech - by proactively identifying opportunities and building data infrastructure for insights and AI usage. You will be an influential member of the Growth Analytics team, mentoring other team members and leading the adoption of new technologies and ways of working.

Lettuce share what this role will be responsible for

• Lead Data Quality & Strategic Optimization: Act as the final authority on SQL/Python reviews and own strategic systems. You will resolve systemic deficiencies, manage non-functional requirements like global scalability, and make high-level design trade-offs in ambiguous, high-risk situations.
• Architect Robust Data Models & AI Foundations: Drive the design of scalable models and create AI-ready data foundations. You will transform data through medallion architecture (Bronze to Gold) to ensure high-quality feature engineering and "truth sets" that intuitively reflect complex business logic.
• Drive Pipeline Stewardship & Best Practices: Take ultimate accountability for pipeline reliability and define the tooling roadmap. You will lead high-impact migrations, set monitoring strategies for latency and throughput, and evangelize the adoption of new technologies like DBT and observability tools.
• Enable Cross-Functional Strategy & Mentor the Team: Partner with leadership to translate business goals into technical roadmaps while you mentor and scale the team. You will develop self-service tools for analysts and initiate organizational changes to improve delivery speed and data accuracy.
  
  
  

Sound a-peeling? Here's what we're looking for

• Leadership in Analytics Engineering & Change Agency: 7+ years of experience with a proven track record of owning technical strategy across multiple business domains. You don’t just manage the status quo; you actively simplify codebases, resolve root-cause deficiencies, and lead teams through complex migrations.
• Mastery of the Modern Data Stack & AI Proficiency: Expert-level SQL and Python skills with deep experience refactoring complex pipelines (e.g., Snowflake, dbt). You possess a strong understanding of the data lifecycle for AI and are familiar with LLM-integrated data workflows.
• Strategic Problem Solving & Exceptional Communication: Ability to solve high-complexity technical problems and anticipate bottlenecks before they hit the business. You can effectively advise Senior Leadership, bridging the gap between deep technical architecture and business value.
• Operational Excellence Mindset & Pragmatism: A focus on "metrics that matter" (P0 pipelines, MTTR, documentation) combined with the business acumen to know when to drive standards and when to adapt for optimal outcomes.

Let’s cut to the cheese, this is why you'll love it here

• Box Discount - Amazing discounts on 1 box per week! 75% discount on weekly HelloFresh and Chefs Plate meal kits AND 50% off weekly Factor meal box.
• Health & Wellness - Health & Dental benefits from day 1, a Health Spending Account, unlimited access to the Headspace app to meet your self-care needs, and 25% discount on GoodLife fitness memberships!
• Vacation & PTO - Time off is also an important part of self-care! We offer generous vacation and PTO to help you create a good work-life balance. 
• Family Benefits - A parental leave top-up program for expectant parents.
• Growth & Development - We support your career progression and invest in your continued learning through experiences and initiatives owned by our dedicated L&D team
• Work Hard & Have Fun - From team socials to engaging company days, you’ll have plenty of opportunity to experience the fun!
• Diversity & Inclusion Initiatives - With impactful ERG’s like FreshPride, Women Empowered and LIMES, we are committed to our diversity, equity & inclusion efforts.
• Food Puns - this one is kind of a big dill if you haven’t already noticed. We even have some punny meeting room names!
  
  

Flexible Hybrid Approach

At HelloFresh, we know that flexible work arrangements are essential in enabling you to do your best work, while balancing your personal and life needs. Offering remote work flexibility, along with the opportunity to interact and collaborate in the office are all a part of creating a great employee experience. 

To meet these needs, we are pleased to provide Flexible Hybrid work. Flexible Hybrid is a people-first approach that is based on choice, trust, personalization, and empowers teams to choose when and how often they work from the office and work from home, in addition to team days and company days. This means a minimum of 2 days in office per week, with most teams in office between 2-3 days a week.

#LI-HYBRID

HelloFresh Canada uses AI-integrated technology to help us process and evaluate applications more efficiently. This includes tools that screen and assess candidate qualifications based on the requirements for this role. While these tools assist our workflow, all final selection decisions are made by our hiring team.

This is a posting for an existing vacancy. We are actively seeking to fill this position.

The Growth Tech Alliance's goal is to enable HelloFresh to drive smarter marketing through AI-powered automation, intelligent systems, and advanced optimization. We've pioneered cutting-edge approaches to programmatic campaign optimization using state-of-the-art AI/ML technologies and are now scaling these capabilities across our global marketing operations. Our team’s key responsibilities include designing, building, maintaining autonomous decision-making systems, advanced ML models for marketing optimization, and real-time intelligence that drives measurable business impact. We work at the intersection of modern AI architectures, deep statistical modelling, and enterprise-scale ML operations.

S'more about the team

As a Senior Data Scientist in AdTech, you will design, build, and deploy production-grade machine learning models that drive significant marketing ROI. You will provide critical expertise in advancing our intelligent marketing optimization systems, focusing on the entire ML lifecycle from data preprocessing and feature engineering to large-scale deployment and performance monitoring. By translating complex marketing challenges into robust production systems, you will ensure our AI-driven capabilities deliver measurable business impact and enhanced efficiency at a  global scale

Lettuce share what this role will be responsible for

• Develop, build, and iterate on advanced machine learning models across core adtech domains to optimize marketing performance and contribute to the orchestration of highly efficient marketing workflows.
• Design and implement ML models for Media Optimization, and contribute to their operationalization into high-impact production systems.
• Contribute to Creative Automation efforts by building and enhancing predictive AI models to guide our global production studios.
• Design and build ML models for Value Optimization to intelligently isolate high-value customers.
• Adhere to and contribute to the team's ML operations (MLOps) practices, focusing on experiment tracking, system observability, and model reliability in production.
• Rapidly prototype innovative machine learning solutions, including Gen AI-forward approaches, and integrate them into our existing, orchestrated multi-agent systems to enable complex autonomous workflows.
• Collaborate closely with Product, Engineering, and Marketing to identify high-impact programmatic automation opportunities and execute robust A/B testing and experimentation designs for models in high-noise environments.
• All other duties, as assigned

Sound a-peeling? Here's what we're looking for

• MSc or equivalent experience in a quantitative discipline with proven experience building and deploying AI/ML systems from prototype to production at scale
• Expert proficiency in Python, PySpark, and SQL, hands-on experience with cloud environments (GCP, AWS, or Azure), and practical experience with modern machine learning frameworks such as HuggingFace, TensorFlow or similar.
• Expertise in applied machine learning relevant to AdTech, including predictive modeling, optimization algorithms, and modern LLM capabilities preferred.
• Proven experience tackling complex marketing data problems, such as algorithmic budget pacing, LTV prediction pipelines, or AI-driven media optimization systems.
• Strong foundation in statistical analysis and experimentation, with practical experience designing A/B tests to validate the incremental business impact of algorithmic systems
• Demonstrated ability to effectively communicate intricate analytical findings to diverse audiences, bridging the gap between deep technical implementation and core business KPIs
• Track record of building production ML systems with robust practices, demonstrating a bias for action and extreme ownership, treating the business outcomes of your algorithms with a true Founder Mentality
• Experience with programmatic advertising ecosystems, marketing analytics, and the operational aspects of running performance-critical ML models in high-traffic environments

Let’s cut to the cheese, this is why you'll love it here

• Box Discount - Amazing discounts on 1 box per week! 75% discount on weekly HelloFresh and Chefs Plate meal kits AND 50% off weekly Factor meal box.
• Health & Wellness - Health & Dental benefits from day 1, a Health Spending Account, unlimited access to the Headspace app to meet your self-care needs, and 25% discount on GoodLife fitness memberships!
• Vacation & PTO - Time off is also an important part of self-care! We offer generous vacation and PTO to help you create a good work-life balance. 
• Family Benefits - A parental leave top-up program for expectant parents.
• Growth & Development - We support your career progression and invest in your continued learning through experiences and initiatives owned by our dedicated L&D team
• Work Hard & Have Fun - From team socials to engaging company days, you’ll have plenty of opportunity to experience the fun!
• Diversity & Inclusion Initiatives - With impactful ERG’s like FreshPride, Women Empowered and LIMES, we are committed to our diversity, equity & inclusion efforts.
• Food Puns - this one is kind of a big dill if you haven’t already noticed. We even have some punny meeting room names!

Flexible Hybrid Approach

At HelloFresh, we know that flexible work arrangements are essential in enabling you to do your best work, while balancing your personal and life needs. Offering remote work flexibility, along with the opportunity to interact and collaborate in the office are all a part of creating a great employee experience. 

To meet these needs, we are pleased to provide Flexible Hybrid work. Flexible Hybrid is a people-first approach that is based on choice, trust, personalization, and empowers teams to choose when and how often they work from the office and work from home, in addition to team days and company days. This means a minimum of 2 days in office per week, with most teams in office between 2-3 days a week.

#LI-HYBRID

HelloFresh Canada uses AI-integrated technology to help us process and evaluate applications more efficiently. This includes tools that screen and assess candidate qualifications based on the requirements for this role. While these tools assist our workflow, all final selection decisions are made by our hiring team.

This is a posting for an existing vacancy. We are actively seeking to fill this position.

This is Engineering at Lattice

At Lattice, we build software that helps people and organizations thrive. Our engineering team values maintainable systems, strong collaboration, and thoughtful product experiences.

As we expand AI-powered capabilities across our platform, security is a core part of how we design, build, and operate our product. Our Product Security team partners closely with engineering to ensure we ship features that are secure by default and resilient in production.

What You Will Do

You will work closely with product and platform engineering teams to improve the security of Lattice’s applications and services.

Product Security & Engineering Partnership

• Partner with engineers to identify, triage, and remediate security issues in product features and services
• Participate in security reviews and threat modeling for new features and systems
• Perform security-focused code reviews and help identify common vulnerabilities
• Contribute to secure-by-default patterns, libraries, and tooling in our TypeScript-based stack

Security Tooling & Operations

• Help implement and operate security tooling (SAST, DAST, dependency scanning, etc.)
• Support vulnerability management workflows, including internal findings and bug bounty reports
• Assist in investigating security issues and assessing risk and impact

Cloud & Platform Security

• Collaborate with platform and infrastructure teams to improve application and cloud security posture
• Contribute to improving security practices in AWS-based environments

AI/LLM Security

• Assist in identifying and mitigating risks in AI/LLM-powered features, including prompt injection, data leakage, and unsafe output handling
• Apply emerging best practices (OWASP Top 10 for LLM Applications) to real product use cases

Security Enablement

• • Contribute to security guidance, documentation, and training for engineering teams
  • Help improve how security is integrated into the development lifecycle

What You Will Bring to the Table

Experience that is important for you to have at some level:

• 1–3+ years of experience in product security, application security, or software engineering
• Experience writing and maintaining code in JavaScript/TypeScript (or similar languages like Python or Ruby)
• Familiarity with common web and API vulnerabilities (e.g., OWASP Top 10)
• Exposure to security testing tools (SAST, DAST, dependency scanning, etc.)
• Experience working in or with cloud environments (AWS or similar)

Technical Approach

• Ability to identify common security risks and suggest practical mitigations
• Understanding of secure coding practices and basic security controls
• Interest in how security decisions impact real-world product systems

Collaboration & Growth

• Strong communication skills and ability to work closely with engineering teams
• Willingness to ask questions, learn quickly, and take ownership of well-scoped problems
• Ability to contribute to team discussions and share security context effectively

Experience that would be nice to have:

• Experience with modern web architectures (Next.js, NestJS, GraphQL)
• Familiarity with containerization or Kubernetes
• Experience or interest in AI/LLM security, including

----

The estimated annual cash salary for this role is $116,500 - $154,000. This position is also eligible for incentive stock options, subject to the terms of Lattice’s applicable plans

Benefits: The Company offers the following benefits for this position, subject to applicable eligibility requirements: Medical insurance; Dental insurance; Vision insurance; Life, AD&D, and Disability Insurance; Emergency Weather Support; Wellness Apps; Paid Parental Leave, Paid Time off inclusive of holidays and sick time; Commuter & Parking Accounts; Lunches in the Office; Internet and Phone Stipend; 401(k) retirement plan; Financial Planning; Learning & Development Budget

*Note on Pay Transparency:

Lattice provides an estimate of the compensation for roles that may be hired as required by state regulations. Compensation may vary based on (a) location, as Lattice factors in specific location when benchmarking compensation for most roles; (b) individual candidate skills and qualifications; and (c) individual candidate experience.

Additionally, Lattice leverages current market data to determine compensation, so posted compensation figures are subject to change as new market data becomes available. The salary, other compensation, and benefits information is accurate as of the date of this posting. Lattice reserves the right to modify this information at any time, subject to applicable law.

#LI-remote

About the Role

In 2026, Orium is investing in AI and automation to improve how SG&A functions operate across the organization.

Our goal is to build agentic systems that support real human decision-making — including a unified entry point and two-way workflows that allow agents, humans, and systems to interact reliably. We’re approaching this work intentionally, with strong foundations around trust, escalation, and human judgment.

We’ve completed early experimentation through pilots and demos, and we’re now looking for someone to help turn that learning into durable, production-ready capabilities.

This is a contract role focused on hands-on execution with strong technical ownership. As a Senior AI Systems Engineer you’ll work hands-on to design and build the technical foundations of these systems, partnering closely with internal stakeholders to translate evolving needs into reliable, scalable agentic workflows. The focus of this engagement is to accelerate the build-out of core agentic capabilities and to establish strong technical foundations over a defined period.

Role Details:

• Type: Contract (Part-Time)
• Duration: ~16 weeks
• Expected Commitment: ~20 hours per week
• Potential for extension or future engagement based on outcomes

Key Responsibilities

Agentic System Development

• Partner in shaping the technical approach and architecture of agentic systems, helping translate evolving needs into practical, scalable solutions.
• Design and implement agentic workflows that support two-way interaction between humans, agents, and internal systems.
• Build and orchestrate workflow logic using tools and frameworks such as Zapier + code, n8n (or similar), APIs, and event-driven architectures.
• Partner to integrate people-focused agentic workflows into a cohesive, reliable entry-point experience.

Systemization & Reliability

• Bring a technical perspective to early-stage ideas and prototypes, helping assess feasibility, trade-offs, and paths to production.
• Help evolve early implementations into more robust, maintainable, and production-ready systems.
• Help establish and document patterns for reliability, observability, and safe failure in agentic workflows.
• Ensure implementations align with defined trust models, escalation rules, and human-in-the-loop principles.

AI & Automation Craft

• Work hands-on with LLMs, prompts, and agent behaviour to prioritize correctness, clarity, and human accountability.
• Evaluate and integrate tools, frameworks, and platforms that support agentic patterns as the system matures.
• Contribute to and document shared standards and patterns for AI-augmented systems at Orium.
• Design and evolve retrieval and indexing approaches (e.g., RAG, structured knowledge sources) to ensure agents operate on accurate, relevant, and up-to-date context.

Skills & Experience

• Experience building, integrating, or supporting AI / LLM-powered systems, with an emphasis on reliability, validation, and safe failure.
• Proven experience taking systems from prototype to production, including defining architecture, managing trade-offs, and ensuring reliability at scale.
• Strong experience building backend systems, workflows, or integrations, including APIs, event-driven systems, and automation frameworks.
• Comfortable working with orchestration tools and workflow engines (e.g., Zapier + code, n8n, Temporal, Airflow, or similar), including extending platforms with custom logic where needed.
• Experience designing or contributing to system architecture, particularly in integration-heavy or distributed systems.
• Strong proficiency in JavaScript/Typescript, including building and deploying backend services, integrations, or extensions to support workflow and automation systems.
• Comfortable taking ownership in ambiguous problem spaces, helping define the path forward rather than waiting for fully defined requirements.
• Strong collaborator who enjoys building in partnership with product, domain, and systems owners.

Is the Role a Fit for You?

You’ll be a strong fit for this role if you:

• Think with a product mindset, not a ticket mindset. You take the time to understand stakeholder needs and real-world workflows before building solutions.
• Are comfortable working in ambiguity. You can take rough ideas or early prototypes and shape them into clear, working systems.
• Think in systems. You naturally connect tools, people, and processes into cohesive, scalable workflows.
• Take ownership and drive outcomes. You define the path forward and see things through to production, not just implementation.
• Balance speed with sound judgment. You move quickly while being thoughtful about reliability, failure modes, and human impact, especially when working with AI systems.

Compensation and Hiring Transparency 

• Expected Compensation (Mexico): Compensation will be offered in MXN, aligned with local market benchmarks and the employment model. Final compensation will consider experience, skills, location, internal equity, and business needs.
• Use of AI in Hiring: To keep the process efficient and focused on human connection, we use AI-enabled and automated tools for tasks like candidate communications and scheduling, interview note-taking, and summarizing feedback for hiring teams. Our recruiters and hiring managers review all information, and humans make every hiring decision.
• Vacancy Status: This posting is for an existing vacancy we are actively hiring for.

Committed to an Inclusive Workplace

We are committed to fostering an inclusive and accessible workplace. We provide reasonable accommodations throughout the hiring process in accordance with applicable local laws. If you require accommodations, we will work with you to meet your needs.

Committed to Social and Environmental Stewardship

Orium is committed to promoting and working towards a more socially and environmentally sustainable future. All employees are expected to make decisions and take actions in relation to their role and work that follow through on this commitment.

#LI-Remote

About the Role

In 2026, Orium is investing in AI and automation to improve how SG&A functions operate across the organization.

Our goal is to build agentic systems that support real human decision-making — including a unified entry point and two-way workflows that allow agents, humans, and systems to interact reliably. We’re approaching this work intentionally, with strong foundations around trust, escalation, and human judgment.

We’ve completed early experimentation through pilots and demos, and we’re now looking for someone to help turn that learning into durable, production-ready capabilities.

This is a contract role focused on hands-on execution with strong technical ownership. As a Senior AI Systems Engineer you’ll work hands-on to design and build the technical foundations of these systems, partnering closely with internal stakeholders to translate evolving needs into reliable, scalable agentic workflows. The focus of this engagement is to accelerate the build-out of core agentic capabilities and to establish strong technical foundations over a defined period.

Role Details:

• Type: Contract (Part-Time)
• Duration: ~16 weeks
• Expected Commitment: ~20 hours per week
• Potential for extension or future engagement based on outcomes

Key Responsibilities

Agentic System Development

• Partner in shaping the technical approach and architecture of agentic systems, helping translate evolving needs into practical, scalable solutions.
• Design and implement agentic workflows that support two-way interaction between humans, agents, and internal systems.
• Build and orchestrate workflow logic using tools and frameworks such as Zapier + code, n8n (or similar), APIs, and event-driven architectures.
• Partner to integrate people-focused agentic workflows into a cohesive, reliable entry-point experience.

Systemization & Reliability

• Bring a technical perspective to early-stage ideas and prototypes, helping assess feasibility, trade-offs, and paths to production.
• Help evolve early implementations into more robust, maintainable, and production-ready systems.
• Help establish and document patterns for reliability, observability, and safe failure in agentic workflows.
• Ensure implementations align with defined trust models, escalation rules, and human-in-the-loop principles.

AI & Automation Craft

• Work hands-on with LLMs, prompts, and agent behaviour to prioritize correctness, clarity, and human accountability.
• Evaluate and integrate tools, frameworks, and platforms that support agentic patterns as the system matures.
• Contribute to and document shared standards and patterns for AI-augmented systems at Orium.
• Design and evolve retrieval and indexing approaches (e.g., RAG, structured knowledge sources) to ensure agents operate on accurate, relevant, and up-to-date context.

Skills & Experience

• Experience building, integrating, or supporting AI / LLM-powered systems, with an emphasis on reliability, validation, and safe failure.
• Proven experience taking systems from prototype to production, including defining architecture, managing trade-offs, and ensuring reliability at scale.
• Strong experience building backend systems, workflows, or integrations, including APIs, event-driven systems, and automation frameworks.
• Comfortable working with orchestration tools and workflow engines (e.g., Zapier + code, n8n, Temporal, Airflow, or similar), including extending platforms with custom logic where needed.
• Experience designing or contributing to system architecture, particularly in integration-heavy or distributed systems.
• Strong proficiency in JavaScript/Typescript, including building and deploying backend services, integrations, or extensions to support workflow and automation systems.
• Comfortable taking ownership in ambiguous problem spaces, helping define the path forward rather than waiting for fully defined requirements.
• Strong collaborator who enjoys building in partnership with product, domain, and systems owners.

Is the Role a Fit for You?

You’ll be a strong fit for this role if you:

• Think with a product mindset, not a ticket mindset. You take the time to understand stakeholder needs and real-world workflows before building solutions.
• Are comfortable working in ambiguity. You can take rough ideas or early prototypes and shape them into clear, working systems.
• Think in systems. You naturally connect tools, people, and processes into cohesive, scalable workflows.
• Take ownership and drive outcomes. You define the path forward and see things through to production, not just implementation.
• Balance speed with sound judgment. You move quickly while being thoughtful about reliability, failure modes, and human impact, especially when working with AI systems.

Compensation and Hiring Transparency 

• Compensation: Contract rates are determined based on experience, engagement scope, duration, and time commitment. Rate discussions will take place during initial conversations.
• Use of AI in Hiring: To keep the process efficient and focused on human connection, we use AI-enabled and automated tools for tasks like candidate communications and scheduling, interview note-taking, and summarizing feedback for hiring teams. Our recruiters and hiring managers review all information, and humans make every hiring decision.

Committed to an Inclusive Workplace

We are committed to fostering an inclusive and accessible environment as we build a workforce that reflects the diversity of the community in which we live, including those with disabilities. We are dedicated to providing accommodations in all parts of the hiring process in accordance with the Accessibility for Ontarians with Disabilities Act and the Ontario Human Rights Code. If you require any accommodation, we will work with you to meet your needs.

Committed to Social and Environmental Stewardship

Orium is committed to promoting and working towards a more socially and environmentally sustainable future. All individuals engaged by Orium are expected to make decisions and take actions in relation to their role and work that follow through on this commitment.

#LI-Remote

Okta is seeking a highly proficient GEO Content Specialist to execute content-focused Generative Engine Optimization (GEO) strategies for Okta and Auth0. This is a mid-level individual contributor role focused on ensuring content is optimized for visibility and retrieval in the evolving landscape of AI Search/GEO/AEO. The ideal candidate is a reliable self-starter with a strong understanding of content, SEO, and the mechanisms of Large Language Models (LLMs).

Core Responsibilities & Execution

• Content Optimization:
• Execute the strategy for structuring and optimizing content to promote content retrievability by LLMs
• Develop and refine content blocks to be machine-parsable and aligned with semantic density and emerging AI answer formats.
• Understand how content must be shaped for LLM visibility and apply best practices while adhering to brand and quality standards.
• Identify opportunities by reviewing GEO prompt data, analyzing competitors, and thinking creatively about content needs for the business
• GEO Knowledge & Application:
• Maintain a working knowledge of how LLMs function, relevant KPIs, and content-related GEO best practices.
• Apply concepts such as vector embeddings, RAG, grounding, chunks, passages, and citations in daily content work.
• Stay current on industry changes related to GEO/AEO/AIO and the future of organic visibility.
• Data & Workflow:
• Utilize a data-driven approach to execute content tasks and identify content performance trends.
• Collaborate with Content and Digital Strategy teams to ensure optimized content is published effectively.
• Manage assigned content tasks effectively, meeting deadlines and quality standards.
• Leverage AI in content analysis, editing and production workstreams to improve efficiency and output

Qualifications

• 4+ years of professional experience in SEO, digital marketing, or content strategy, with a focus on content optimization and/or content development
• Understands how content is rewarded in both LLMs and modern-day search ranking algorithms (this position is not about traditional SEO keyword optimization)
• Familiarity with current GEO concepts and the role of LLMs in search
• Working knowledge of SEO/AI Search platforms such as SEMRush, BrightEdge, Ahrefs, Profound, and Google Search Console.
• Proficiency in data analysis and insights gathering for content output and performance tracking
• Strong communication skills, with the ability to articulate content requirements and results clearly
• Experience using Adobe Experience Manager (AEM) or a similar enterprise-level CMS.
• Background in the Identity and Access Management (IAM), B2B marketing, SAAS, or the cybersecurity domain is preferred, but not required.

#LI - Hybrid

#P24088_3363970

Tucows Domains is the world’s largest wholesale domain registrar, responsible for maintaining the health, neutrality, and openness of an important—but largely invisible part of the Internet: the domain name system (DNS).

As part of Tucows—one of the world’s largest Internet companies—Tucows Domains has a rich history of helping make the Internet better, operating globally under the Ascio, Enom, Hover and OpenSRS brands.

We embrace a people-first philosophy that is rooted in respect, trust, and flexibility. We believe that whatever works for our employees is what works best for us. It’s also why the majority of our roles are remote-first, meaning you can work from anywhere you can connect to the Internet! Today, over one thousand people from over 20 countries are part of our team.

If this sounds exciting to you, join the herd! 

About the Opportunity

We’re looking for a passionate Intermediate Software Engineer specializing in Artificial Intelligence to join our growing team. In this role, you’ll help shape and build innovative AI-powered systems that transform how users interact with domain-related tools and services. You’ll work both with your team of forward-thinking engineers and with colleagues across business functions to prototype, develop, and deploy intelligent solutions using both commercial and open-source models along with modern infrastructure.

This is a remote position open to applicants in Canada or USA. 

What You’ll Do

• Design and build AI-driven features for our domain services platform using Python and Golang.
• Integrate and fine-tune open-source models with cutting-edge architectures via tools like Ollama.
• Research, evaluate, and implement emerging AI technologies that align with our vision for smarter, more intuitive products and services.
• Collaborate with internal stakeholders and fellow engineers to rapidly prototype and iterate on machine learning and LLM-based features.
• Contribute to a modern AI development stack, ensuring scalability, performance, and ethical usage of models.
• Actively participate in the open-source ecosystem and bring relevant tools and techniques back to the team.
• Implement software solutions with “intelligent” features, helping teams automate tedious and repetitive tasks.

Key Skills and Experience

• Bachelor’s degree in software engineering, computer science, or related field, with strong proficiency in Python and Golang.
• 3+ years of professional software engineering experience in production environments.
• Solid understanding of modern AI/ML/LLM concepts, particularly transformer-based and open-source models.
• Hands-on experience with frameworks such as TensorFlow, Hugging Face, or similar.
• Experience using open-source models (e.g., LLaMA, Mistral, Mixtral) in real-world applications.
• Strong foundation in software design principles and service-oriented architecture.
• Experience contributing to scalable system and component-level architecture.
• Ability to design and build RESTful APIs for model serving and AI-enabled workflows.
• Understanding of API best practices, including versioning, security, and error handling.
• Working knowledge of relational and/or SQL databases and data modeling for AI use cases.
• Experience with containerization and cloud-native deployment of AI services.
• Strong collaboration, communication skills, and enthusiasm for emerging AI technologies.

The base salary range for this position is $100,000 - $115,000 USD for US residents OR $100,350 - $111,500 CAD for Canadian residents Other countries will differ. Range may vary on a number of factors including, but not limited to: location, experience and qualifications. Tucows believes in a total rewards offering that includes fair compensation and generous benefits

Want to know more about what we stand for? At Tucows we care about protecting the open Internet, narrowing digital divide, and supporting fairness and equality.

We also know that diversity drives innovation. We are committed to inclusion across race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status or disability status. We celebrate multiple approaches and diverse points of view.

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform crucial job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.

Tucows and its subsidiaries participate in the E-verify program for all US employees.

Learn more about Tucows, our businesses, culture and employee benefits on our site here.

Tucows Domains is the world’s largest wholesale domain registrar, responsible for maintaining the health, neutrality, and openness of an important—but largely invisible part of the Internet: the domain name system (DNS).

As part of Tucows—one of the world’s largest Internet companies—Tucows Domains has a rich history of helping make the Internet better, operating globally under the Ascio, Enom, Hover and OpenSRS brands.

We embrace a people-first philosophy that is rooted in respect, trust, and flexibility. We believe that whatever works for our employees is what works best for us. It’s also why the majority of our roles are remote-first, meaning you can work from anywhere you can connect to the Internet! Today, over one thousand people from over 20 countries are part of our team.

If this sounds exciting to you, join the herd! 

About the Opportunity

We’re looking for a passionate Intermediate Software Engineer specializing in Artificial Intelligence to join our growing team. In this role, you’ll help shape and build innovative AI-powered systems that transform how users interact with domain-related tools and services. You’ll work both with your team of forward-thinking engineers and with colleagues across business functions to prototype, develop, and deploy intelligent solutions using both commercial and open-source models along with modern infrastructure.

This is a remote position open to applicants in Canada or USA. 

What You’ll Do

• Design and build AI-driven features for our domain services platform using Python and Golang.
• Integrate and fine-tune open-source models with cutting-edge architectures via tools like Ollama.
• Research, evaluate, and implement emerging AI technologies that align with our vision for smarter, more intuitive products and services.
• Collaborate with internal stakeholders and fellow engineers to rapidly prototype and iterate on machine learning and LLM-based features.
• Contribute to a modern AI development stack, ensuring scalability, performance, and ethical usage of models.
• Actively participate in the open-source ecosystem and bring relevant tools and techniques back to the team.
• Implement software solutions with “intelligent” features, helping teams automate tedious and repetitive tasks.

Key Skills and Experience

• Bachelor’s degree in software engineering, computer science, or related field, with strong proficiency in Python and Golang.
• 3+ years of professional software engineering experience in production environments.
• Solid understanding of modern AI/ML/LLM concepts, particularly transformer-based and open-source models.
• Hands-on experience with frameworks such as TensorFlow, Hugging Face, or similar.
• Experience using open-source models (e.g., LLaMA, Mistral, Mixtral) in real-world applications.
• Strong foundation in software design principles and service-oriented architecture.
• Experience contributing to scalable system and component-level architecture.
• Ability to design and build RESTful APIs for model serving and AI-enabled workflows.
• Understanding of API best practices, including versioning, security, and error handling.
• Working knowledge of relational and/or SQL databases and data modeling for AI use cases.
• Experience with containerization and cloud-native deployment of AI services.
• Strong collaboration, communication skills, and enthusiasm for emerging AI technologies.

The base salary range for this position is $100,000 - $115,000 USD for US residents OR $100,350 - $111,500 CAD for Canadian residents Other countries will differ. Range may vary on a number of factors including, but not limited to: location, experience and qualifications. Tucows believes in a total rewards offering that includes fair compensation and generous benefits

Want to know more about what we stand for? At Tucows we care about protecting the open Internet, narrowing digital divide, and supporting fairness and equality.

We also know that diversity drives innovation. We are committed to inclusion across race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status or disability status. We celebrate multiple approaches and diverse points of view.

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform crucial job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.

Tucows and its subsidiaries participate in the E-verify program for all US employees.

Learn more about Tucows, our businesses, culture and employee benefits on our site here.

Overview

Instacart’s Data Infrastructure organization builds and operates the systems that power our company’s data ecosystem, including a modern open data lakehouse on Apache Iceberg, a multi-engine compute platform for stream and analytical workloads, and self-serve tooling that helps Product, Data Science, ML, Ads, Finance, and engineering teams move fast with data.

We’re looking for a Staff Software Engineer, Data Infrastructure to join our Data Governance and Foundations Team. In this role, you’ll serve as a senior technical leader owning the architecture and delivery of our open lakehouse foundation, governance and access patterns, and multi-engine compute strategy—balancing today’s reliability with the next three to five years of scale, maturity, and cost efficiency.

You’ll collaborate closely with engineering leadership and stakeholders across Data Science, ML Platform, Ads Infrastructure, Finance Engineering, Product Engineering, and Security. You’ll operate with a high degree of ownership in a fast-paced environment where architectural decisions have real technical and financial consequences. If you thrive on complex, high-scale challenges and roll-up-your-sleeves execution, this is a chance to shape the backbone of Instacart’s data platform.

Our stack includes technologies such as Apache Iceberg, Apache Flink, Trino, ClickHouse, Apache Kafka, Apache Spark, Snowflake, Databricks, Confluent, Airflow, dbt, Delta Lake, Scala, Python, Postgres, and AWS. You’ll join a focused team of 7 engineers that values pragmatism, clarity, and impact.

About the Job

• Translate Instacart’s data strategy (e.g., monetization, federated access, real-time) into an actionable multi-year architecture roadmap; align with leadership while evolving the platform for scale, maturity, and cost efficiency.
• Own the open lakehouse foundation: define and deliver unified table formats, storage governance, and a multi-engine compute portfolio (interactive, batch, streaming) that enables portability and prevents lock-in.
• Drive real-time and streaming infrastructure for critical use cases (Ads, Fraud, ML): set deployment patterns, SLAs, and operational practices that balance performance, availability, and spend.
• Pioneer AI-native data infrastructure engineering by applying LLM/AI tools to the platform lifecycle—accelerating development, automation, observability, and cost optimization—and partnering to embed AI-powered capabilities into the platform.
• Elevate engineering excellence: lead architecture reviews, mentor senior/staff engineers, influence hiring, and clearly communicate complex trade-offs to both technical and executive audiences to ensure cross-org alignment.

About You

Minimum Qualifications

• 5+ years of software engineering experience building and operating data infrastructure or distributed systems at production scale.
• Hands-on expertise with modern data lakehouse architectures and open table formats (e.g., Apache Iceberg, Delta Lake, Hudi) and with distributed query/compute engines (e.g., Trino, Spark, ClickHouse), including performance tuning and production reliability.
• Experience with event-driven and streaming infrastructure (e.g., Kafka, Flink) for real-time pipelines and serving systems.
• Proven ownership of major platform transitions or migrations (build vs. buy, migration design, risk management) delivered to production.
• Ability to build cost/benefit and TCO models for infrastructure investments and to drive alignment via clear architecture docs and strategy memos across multiple teams and leadership levels.

Preferred Qualifications

• Experience designing platform-level governance controls and familiarity with compliance frameworks (e.g., SOX, CPRA, GDPR).
• FinOps experience optimizing data platform spend, including managing multi-million dollar infrastructure budgets and negotiating vendor contracts.
• Deep SQL proficiency and strong skills in Python or Scala for systems-level development.
• Experience with orchestration (e.g., Apache Airflow) and data transformation pipelines (e.g., dbt) in large-scale production environments.
• Bachelor’s, Master’s, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or equivalent practical experience.

#LI-Remote

Tucows Domains is the world’s largest wholesale domain registrar, responsible for maintaining the health, neutrality, and openness of an important—but largely invisible part of the Internet: the domain name system (DNS).

As part of Tucows—one of the world’s largest Internet companies—Tucows Domains has a rich history of helping make the Internet better, operating globally under the Ascio, Enom, Hover and OpenSRS brands.

We embrace a people-first philosophy that is rooted in respect, trust, and flexibility. We believe that whatever works for our employees is what works best for us. It’s also why the majority of our roles are remote-first, meaning you can work from anywhere you can connect to the Internet! Today, over one thousand people from over 20 countries are part of our team.

If this sounds exciting to you, join the herd!

About the Opportunity

At Tucows, we have spent three decades building the software and infrastructure that keeps the internet running. We believe in an internet that is open, reliable, and simple. As we integrate Artificial Intelligence into our ecosystem, we aren't looking for superficial implementations; we are looking to build robust, agentic systems that fundamentally improve how millions of users manage their digital identities and connectivity.

We are seeking a Senior AI Engineer to join a dedicated team of engineers building the next generation of intelligent agents that help scale our business. You will bridge the gap between cutting-edge LLM research and production-grade software engineering, leading the development of systems that automate complex tasks with the same reliability our infrastructure is known for.

This is a remote opportunity for applicants in Canada or USA.

What You’ll Do

• System Architecture: Design and implement scalable AI-driven features with a focus on multi-agent systems and advanced RAG architectures.
• Production Excellence: Move beyond the prototype. You will own the full lifecycle of AI services, from model selection and deployment to monitoring in a Kubernetes environment
• Polyglot Engineering: Write clean, maintainable code primarily in Python, while collaborating on core infrastructure services written in Go.
• Ethical AI Leadership: Establish clear standards for data privacy, model bias, and security, including practices like model cards, red-teaming protocols, and privacy impact assessments, ensuring our AI initiatives remain transparent and aligned with our commitment to user trust.

Key Skills & Experience

• Experience: 5+ years of professional software engineering experience, with a proven track record of shipping production-ready applications.
• AI Specialization: Demonstrated expertise working with Large Language Models (LLMs) and agentic frameworks, with a solid understanding of how to apply them to real-world production systems.
• Technical Stack: Advanced proficiency in Python is required. Hands-on experience with Go, or a demonstrated ability to ramp quickly in a Go-heavy environment, is strongly preferred.
• Infrastructure Knowledge: Familiarity with modern DevOps practices, including CI/CD, Docker, and cloud-based inference pipelines on AWS.
• Communication: Exceptional ability to translate complex AI concepts into clear, actionable language for both technical and non-technical audiences. You are comfortable leading discussions, influencing decisions, and mentoring engineers at all levels, making communication as much a part of your craft as the code you write.

​​The base salary range for this position is $120,000 - $145,000 USD for US residents OR $126,090 to $140,100 CAD for Canadian residents. Other countries will differ. Range may vary on a number of factors including, but not limited to: location, experience and qualifications. Tucows believes in a total rewards offering that includes fair compensation and generous benefits

Want to know more about what we stand for? At Tucows we care about protecting the open Internet, narrowing digital divide, and supporting fairness and equality.

We also know that diversity drives innovation. We are committed to inclusion across race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status or disability status. We celebrate multiple approaches and diverse points of view.

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform crucial job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.

We use AI-enabled tools throughout our recruitment process to help us work more efficiently and consistently. These tools support our hiring teams by organizing and reviewing information, while final hiring decisions are always made by people.

Tucows and its subsidiaries participate in the E-verify program for all US employees.

Learn more about Tucows, our businesses, culture and employee benefits on our site here.

Overview

Instacart’s Agentic Commerce team is building innovative new AI Solutions such as Cart Assistant – an enterprise-grade, consumer shopping agent purpose-built for grocery. Cart Assistant will provide hyper-personalized conversational commerce experiences, helping millions of people discover products, plan what to eat, and shop in easier and more engaging ways than ever before. 

We’re looking for a Principal Product Manager to help bring Cart Assistant to life and make it a product that both consumers and retailers love. This is a fast paced, 0->1, highly visible product role working at the intersection of generative AI, consumer experience, and retailer-facing B2B e-commerce products.

In this role, you will immerse yourself in and deeply understand both consumer and retailer needs, as well as the latest and greatest available agentic technologies. You will partner closely with engineering, machine learning, data science, design and research teams to translate these needs and capabilities into a winning product strategy and a prioritized roadmap. You’ll lead execution, experimentation, and product delivery, working closely with retail partners and senior leadership. 

About the Job

• Set and own the roadmap, translating consumer and retailer needs into a clear vision, milestones, and launch plans
• Lead product discovery, uncover customer pain points and market opportunities, and partner with engineering and design to deliver solutions
• Drive measurable results including product adoption and engagement outcomes. Establish and maintain metrics, dashboards, and regular business reviews, using data insights to prioritize, de-risk, and accelerate the roadmap.
• Lead cross-functional execution with Engineering/ML/DS/Design to execute the roadmap, run rapid experiments, ship iterative improvements, and pivot based on learnings
• Partner with ML, model design, and content design to improve core agent performance and behavior using state-of-the-art methods
• Represent the product to senior leadership and external retail partners, communicating strategy, progress, learnings, and needs with clarity and conviction
• Work with business development, market strategy, and GTM teams to align product and GTM plans, maximizing market impact of launches and product advancements 
• Scale Cart Assistant across Instacart surfaces and products, driving top line business impact for Instacart and our retail partners

About You

Minimum Qualifications

• 8+ years of product management experience
• 5+ years of experience building and shipping consumer-facing commerce products end-to-end, with 2+ years building LLM-powered products in production 
• Proven track record launching at least one 0-to-1 product to general availability with measurable impact on adoption, conversion, revenue, or GTV
• Technical fluency with AI/ML systems and data flows; ability to partner with engineering and machine learning on dependencies and scope tradeoffs 
• Experience defining product OKRs, with significant experience using experimentation to improve products and achieve desired outcomes
• Exceptional communication and presentation skills with senior leadership and external enterprise partners
• Bachelor’s degree in a technical, quantitative, or related field, or equivalent practical experience

Preferred Qualifications

• Experience across both consumer products and B2B/enterprise offerings
• Background spanning startup and large company environments
• Domain expertise in ecommerce, retail, grocery, or marketplace dynamics
• Experience building or improving LLM agent systems and products
• Familiarity with experimentation at scale (A/B testing) and with trust, safety, privacy, and compliance considerations for GenAI products.

#LI-Remote

About the Role:

As the Enterprise Applications AI Architect, you will lead the integration of AI and automation across Gusto’s enterprise applications ecosystem, transforming how internal systems connect, communicate, and operate. Sitting within the IT and Enterprise Applications organization, you will partner closely with Product, Engineering, Finance, People Tech, and Operations to bridge business needs with AI driven solutions. You will act as the connector between business requirements and AI frameworks, designing Model Context Protocols (MCPs) and AI agents that make enterprise workflows smarter, faster, and more autonomous. In line with Gusto’s FY26 Enterprise Systems strategy, you will help shift our ERP and Finance systems from reactive workflows to predictive, context aware, and self improving platforms, while ensuring security, compliance, and measurable impact. This role combines hands-on technical execution with strategic systems thinking, using integration fluency, AI literacy, and business empathy to create the connective tissue that allows AI to seamlessly augment enterprise operations.

About the Team:

This role will report to the Enterprise AIT team, a group focused on driving the intelligent transformation of Gusto’s enterprise systems. The Enterprise AIT team is responsible for integrating AI, automation, and advanced analytics across our internal applications ecosystem to improve scalability, efficiency, and decision-making. Partnering closely with Finance, Business Ops, IT, and Security, the team enables Gusto’s enterprise systems to become smarter, more predictive, and more adaptive. This is a new role, designed to expand the team’s capacity to operationalize AI within enterprise workflows and support Gusto’s broader Enterprise Systems strategy.

Here’s what you’ll do day-to-day:

• Translate business needs into AI workflows by partnering with Finance and Business Operations teams to identify automation opportunities and design agentic workflows that improve decision making and reduce manual effort.
• Develop and maintain Model Context Protocols (MCPs) that securely and reliably connect enterprise systems such as NetSuite, Zuora, and Jira to AI agents, with clear documentation and optimization.
• Create and manage intelligent agents that execute or augment core enterprise processes such as onboarding, billing support, and compliance monitoring using large language models and orchestration frameworks.
• Govern the full lifecycle of MCPs and agents, ensuring adherence to enterprise data governance, privacy, and security standards, including SOX compliance, auditability, and appropriate access controls.
• Measure and optimize impact by defining and tracking KPIs such as automation adoption, efficiency gains, agent accuracy, reliability, and cost performance, and using those insights to guide iteration.
• Enable and influence the organization by partnering with IT, Security, and business stakeholders to build reusable AI frameworks, coach teams on safe and effective AI driven workflows, and champion AI first practices across day to day operations.

Here’s what we're looking for:

• 8+ years in Business Systems Analysis, Enterprise Applications, or Automation roles, with a track record of delivering impact in complex environments.
• Demonstrated experience building and maintaining integrations across systems such as Jira, NetSuite, or similar, with a strong grasp of APIs, JSON, and RESTful service design.
• Hands-on knowledge of AI agent frameworks (for example LangChain, CrewAI, Semantic Kernel, MCP) and experience designing or maintaining Model Context Protocols or equivalent frameworks.
• Familiarity with leading LLM platforms (OpenAI, Anthropic, Gemini etc.) and practical experience with prompt engineering.
• Proficiency in Python or JavaScript for automation, orchestration, and building modular, scalable AI workflows that translate complex requirements into executable solutions.
• Strong documentation, analytical, and stakeholder communication skills, with the ability to clearly explain tradeoffs and align technical solutions with business needs.
• Passion for building secure, compliant, and explainable AI systems, embedding risk, privacy, and compliance considerations (including SOX and audit controls) into every solution, with a growth mindset and focus on clarity, iteration, and measurable outcomes.

Our cash compensation amount for this role is targeted at $150,000-$165,000 /yr in Denver & most remote locations, and $185,000-$205,000 /yr for San Francisco, Seattle & New York. Final offer amounts are determined by multiple factors, including candidate experience and expertise, and may vary from the amounts listed above.

About Design at Gusto 

Design at Gusto is made up of over 80 creative, collaborative people who care deeply about our mission to empower small businesses and their employees. We're a cross-functional group that is always looking for opportunities to build understanding and empathy for the people who use Gusto. We don't care much about swim lanes and though we care deeply about quality and craft, we are never precious about it. We work closely with cross-functional partners in Product, Engineering, Data, and Marketing to design, build, and ship experiences that make a real difference. We believe great design can make hard things possible, even delightful.

We are building an AI-native design organization — and we mean that seriously. We're looking for designers who are already working this way: using AI to prototype ideas quickly, shorten customer feedback loops, and ship quality UX directly to customers. This isn't a future aspiration — it's how we work now, and it's changing what the design role looks like at Gusto and across the industry.

About the role:

We’re hiring a Principal Product Designer to lead AI design across Gusto.

This is one of the most senior individual contributor design roles at the company. You’ll define how AI works, behaves, and earns trust across the Gusto platform – starting with Gus, our AI conversational assistant, and expanding into AI-powered workflows embedded in payroll, benefits, HR, and beyond. You’ll shape the interaction model, UX principles, and product direction for AI across Gusto. You will work with senior Product and Engineering leaders to define our AI portfolio. You will develop important AI features that customers will consider and you’ll ship high-impact, customer-facing AI capabilities that help our customers get their work done faster and more effectively, while building their trust in Gusto. These features will help customers finish their tasks faster and build their trust in Gusto.

This role is both strategic and hands-on. We’re looking for someone who can set a long-term UX vision for AI and turn it into real, shipped product that meaningfully improves how small businesses get work done.

Here’s what you’ll do day-to-day:

• Define and evolve the UX vision for our Gus conversational assistant and AI experiences across the Gusto platform.
• Lead and ship Tier 1 AI initiatives from early concept through launch and iteration.
• Design full AI-powered workflows – shaping how users provide input, how model outputs are validated and acted on, and how the experience handles risk, uncertainty, and failure.
• Partner closely with AI Product and Engineering leaders to translate complex technical constraints into intuitive, credible user experiences.
• Establish scalable AI interaction patterns and design principles that teams across Gusto can adopt.
• Write and iterate on prompts in collaboration with engineering, PM, and content design.
• Use AI tooling to accelerate exploration and prototyping, customer feedback loops, and shipping to customers.
• Mentor designers on the AI team and coach designers across Gusto who are shipping AI features.
• Advocate for high-quality, responsible AI experiences across Design and R&D.

Here’s what we're looking for:

• Proven AI product impact: You’ve shipped LLM-driven product experiences to production and can demonstrate measurable impact on adoption, efficiency, or user trust.
• Systems-level thinking: You’ve designed complete AI workflows – not just chat interfaces – and can speak fluently about failure modes, guardrails, user control, and transparency.
• Strategic product influence: You’ve defined UX direction at a portfolio or company level and influenced roadmap, scope, and sequencing decisions in partnership with senior PM and Engineering leaders.
• Technical fluency: You’re comfortable collaborating with highly technical AI engineers. You understand concepts like retrieval, context management, latency, and model reliability, and can translate them into robust UX decisions.
• Builder mindset: You ship. You prototype. You iterate. You’re not interested in defining principles without turning them into real customer impact.
• Organizational leadership: You have enhanced team work quality. You achieved this by coaching team members, setting new standards, and building solid partnerships across different functions.

Compensation Details

At Gusto, we strive to provide rewards that empower employees to achieve their financial and personal goals. We offer competitive compensation packages with a strong emphasis on equity based compensation (ownership in Gusto). To learn more about Gusto’s compensation philosophy and benefits offerings please view our Total Rewards Approach page.

Our cash compensation range for this role is $204,000/yr to $238,000/yr in Denver & most remote locations, and $240,000/yr to $280,000/yr in San Francisco, Seattle & New York. Final offer amounts are determined by multiple factors, including candidate experience and expertise, and may vary from the amounts listed above.

We believe the future of computing must be open, which is why our interns don’t just watch from the sidelines - they help build the core of it. We provide a "code-to-career" pipeline where students collaborate with industry experts to solve high-stakes problems in RISC-V and AI hardware-software co-design. By joining us, you are taking an internship to democratize high-performance computers that are accessible to everyone.

The Project Management Office / Office of the CEO exists to improve organizational effectiveness so Tenstorrent can move faster and make better decisions. In practice, that means improving visibility into company priorities and execution, reducing friction in internal operations, and making important information easier to find, use, and act on across the company.

We are looking for an Applied AI Workflow Automation Intern to build AI-powered tools and automations that reduce manual work, connect fragmented systems, and help Tenstorrent operate more effectively at scale. In this role, you will work on real internal workflows across knowledge systems, productivity tools, and business processes, while exploring how LLMs, retrieval, and workflow automation can improve the way work gets done.

This role is hybrid, based out of Austin, TX,  Fort Collins, CO, Santa Clara, CA, or Toronto, ON offices.

Who You Are

• Pursuing a degree in Computer Science, Computer Engineering, Software Engineering, or a related field
• Comfortable building scripts, tools, or lightweight applications in Python or another programming language
• Interested in applied AI, LLMs, agentic systems, workflow automation, or retrieval systems
• Comfortable working with APIs and integrating across multiple tools and systems
• Able to turn ambiguous, messy workflow problems into practical technical solutions
• Excited to work with both technical and non-technical teams

What We Need

• Build and improve AI-driven workflow automation systems for internal teams
• Design and implement automation using Python, APIs, scripts, and LLM-based tools; experience with n8n or Glean is a plus
• Develop and maintain structured knowledge and retrieval systems that support automation and decision-making; experience with RAG is a plus
• Integrate automation into tools such as Slack, Jira, HR systems, ERPs and internal applications

What You Will Learn

• Own a workflow or process area end-to-end by identifying inefficiencies, designing solutions, building them, and iterating
• How to balance automation, reliability, and human judgment
• How to work with stakeholders across operations, engineering, and business systems
• How to implement guardrails, routing logic, and human-in-the-loop review so systems are reliable in real workflows
• How to measure impact through adoption, time saved, performance, and process improvement metrics

Cresta is on a mission to turn every customer conversation into a competitive advantage by unlocking the true potential of the contact center. Our platform combines the best of AI and human intelligence to help contact centers discover customer insights and behavioral best practices, automate conversations and inefficient processes, and empower every team member to work smarter and faster. Born from the prestigious Stanford AI lab, Cresta's co-founder and chairman is Sebastian Thrun, the genius behind Google X, Waymo, Udacity, and more. Our leadership also includes CEO, Ping Wu, the co-founder of Google Contact Center AI and Vertex AI platform, and co-founder, Tim Shi, an early member of Open AI.

Join us on this thrilling journey to revolutionize the workforce with AI. The future of work is here, and it's at Cresta.

Cresta is building the AI platform for the modern contact center—one of the largest and most critical systems in the global economy. We combine human agents and AI agents to handle customer conversations at scale, helping enterprises improve customer experience, increase revenue, and reduce cost in real time.

This isn’t experimental AI. Our systems run in live production environments, shaping millions of customer interactions every day.

We’re looking for builders who want to take ownership and move fast.

About the Role

As a Software Engineer Intern, you’ll build systems that power real-time, AI-driven customer interactions in contact centers. You’ll work on production infrastructure where latency, reliability, and measurable business outcomes matter.

You may work across key areas such as:

• AI Agents & Automation – systems that handle and assist high-volume customer conversations
• Real-Time Agent Assist – delivering live guidance and insights during interactions
• Conversation Intelligence – extracting insights from millions of conversations
• AI Evaluation & Reliability – improving quality, consistency, and observability of LLM systems
• Platform & Infrastructure – enabling scalable, low-latency AI experiences

Cresta’s platform powers the full contact center workflow—from real-time assistance and automation to post-call analytics and continuous optimization.

You’ll operate in a high-ownership, fast-moving environment where interns are expected to contribute meaningfully, not just observe.

What You’ll Do

• Design and build systems that support real-time AI-powered customer interactions
• Work on features combining LLMs, data systems, and user-facing applications
• Collaborate with engineers, product, and ML teams to ship production-ready solutions
• Build systems for evaluation, monitoring, and continuous improvement of AI behavior
• Optimize for low latency, high throughput, and reliability at scale
• Take ownership of problems end-to-end—from identifying gaps to shipping solutions

What We’re Looking For

• Experience with one or more programming languages (e.g., Python, Go, Java, JavaScript, TypeScript)
• Interest in building user-facing products, backend systems, or real-time/data-intensive applications
• Familiarity with modern web development (frontend and/or backend), APIs, or system design fundamentals
• Understanding of building reliable, maintainable systems—this could include UI/UX quality, API design, or performance considerations
• Curiosity about LLMs, AI agents, or production AI systems (no prior ML experience required)
• Experience using AI-powered developer tools (e.g., Cursor, Claude Code) to accelerate development workflows
• Strong proficiency in agentic coding workflows—effectively collaborating with AI tools to design, implement, and iterate—is a strong plus
• A driver mindset—you proactively identify problems, take initiative, and push work forward rather than waiting for direction
• Strong problem-solving ability and a bias toward action

What You’ll Learn

• How to build and ship production-grade AI systems used in real customer environments
• How to design systems balancing model quality, latency, and reliability
• How AI agents are deployed, evaluated, and improved at scale
• How contact centers evolve from manual workflows to AI-driven operations

What Makes Cresta Different

• AI in production: Our systems operate in live contact centers, not demos
• Hybrid workforce: We’re defining how human and AI agents work together
• Real business impact: We directly influence revenue, cost, and customer experience
• Driver culture: We value people who take initiative, move fast, and own outcomes end-to-end
• Ownership & velocity: Engineers are trusted to ship and make decisions early

Internship Details

• Location: Toronto (remote-friendly; no in-office mandate, but we encourage in-person collaboration)
• Compensation: CAD $30-50/hour
  • Outstanding performers are eligible for return co-op and full-time offers well above our posted range.

• Perks:
• Lunch and dinner can be expensed (up to $25 each) while working in the office
• Well-stocked office with snacks and drinks
• Convenient downtown location near Union Station (public transit accessible)
• PTO: 4 days
• Exposure to cutting-edge AI systems in production
• Potential return offer

Why Join

At Cresta, you won’t just learn about AI—you’ll help build the systems redefining how contact centers operate. From real-time agent assist to autonomous AI agents, your work will directly impact how millions of customer conversations are handled.

Past interns consistently highlight Cresta’s strong engineering culture and ownership-driven environment as a standout compared to their previous internship experiences. We invest in giving interns real responsibility, meaningful projects, and close collaboration with experienced engineers.

If you want to own real problems, ship quickly, and work at the frontier of applied AI, you’ll fit right in.

Application Note

To help us find the best team match, please include a brief note on the type of problems you most enjoy working on. For example:

• Backend / distributed systems / infrastructure
• Frontend / UI engineering / product experience
• Full product development (end-to-end features)
• AI / machine learning / applied LLMs
• Data / analytics / experimentation
• Or anything else you’d like us to highlight

We can’t guarantee specific team placement, but we use this input to help guide matching wherever possible.

This posting will be used to fill a newly-created role.

We have noticed a rise in recruiting impersonations across the industry, where scammers attempt to access candidates' personal and financial information through fake interviews and offers. All Cresta recruiting email communications will always come from the @cresta.ai domain. Any outreach claiming to be from Cresta via other sources should be ignored. If you are uncertain whether you have been contacted by an official Cresta employee, reach out to recruiting@cresta.ai

Overview: 

Guidepoint seeks an experienced Data/AI Engineer as an integral member of the Toronto-based AI team. The Toronto Technology Hub serves as the base of our Data/AI/ML team, dedicated to building a modern data infrastructure for advanced analytics and the development of responsible AI. This strategic investment is integral to Guidepoint’s vision for the future, aiming to develop cutting-edge Generative AI and analytical capabilities that will underpin Guidepoint’s Next-Gen research enablement platform and data products. 

This role demands exceptional leadership and technical prowess to drive the development of next-generation research enablement platforms and AI-driven data products. You will develop and scale Generative AI-powered systems, including large language model (LLM) applications and research agents, while ensuring the integration of responsible AI and best-in-class MLOps. The Senior AI/ML Engineer will be a primary contributor to building scalable AI/ML capabilities using Databricks and other state-of-the-art tools across all of Guidepoint’s products. 

Guidepoint’s Technology team thrives on problem-solving and creating happier users. As Guidepoint works to achieve its mission of making individuals, businesses, and the world smarter through personalized knowledge-sharing solutions, the engineering team is taking on challenges to improve our internal application architecture and create new AI-enabled products to optimize the seamless delivery of our services.

This is a hybrid position based in Toronto. 

What You'll Do 

• Architect and Build Production Systems: Design, build, and operate scalable, low-latency backend services and APIs that serve Generative AI features, from retrieval-augmented generation (RAG) pipelines to complex agentic systems. 

• Own the AI Application Lifecycle: Own the end-to-end lifecycle of AI-powered applications, including system design, development, deployment (CI/CD), monitoring, and optimization in production environments like Databricks and Azure Kubernetes Service (AKS). 

• Optimize RAG Pipelines: Continuously improve retrieval and generation quality through techniques like retrieval optimization (tuning k-values, chunk sizes), using re-rankers, advanced chunking strategies, and prompt engineering for hallucination reduction. 

• Integrate Intelligent Systems: Engineer solutions that seamlessly combine LLMs with our proprietary knowledge repositories, external APIs, and real-time data streams to create powerful copilots and research assistants. 

• Champion LLMOps and Engineering Best Practices: Collaborate with data science and engineering teams to establish and implement best practices for LLMOps, including automated evaluation using frameworks like LLM Judges or MLflow, AI observability, and system monitoring. 

• Evaluate and Implement AI Strategies: Systematically evaluate and apply advanced prompt engineering methods (e.g., Chain-of-Thought, ReAct) and other model interaction techniques to optimize the performance and safety of proprietary and open-source LLMs. 

• Mentor and Lead: Provide technical leadership to junior engineers through rigorous code reviews, mentorship, and design discussions, helping to elevate the team's engineering standards. 

• Influence the Roadmap: Partner closely with product and business stakeholders to translate user needs into technical requirements, define priorities, and shape the future of our AI product offerings. 

 What You'll Bring 

• Experience: A Bachelor’s degree in Computer Science, Engineering, or a related technical field with 6+ years of professional experience; or a Master’s degree with 4+ years of professional experience in backend software engineering and Generative AI. This must include a proven track record of designing, building, and scaling distributed, production-grade systems. 

• Strong Software Engineering Fundamentals: Deep expertise in Python, a major backend framework (e.g., FastAPI, Flask), and asynchronous programming (e.g., asyncio). Proficiency in designing RESTful APIs, microservices, and the complete operational lifecycle, including comprehensive testing, CI/CD (e.g., ArgoCD), observability, monitoring, alerting, maintaining high uptime, and executing zero-downtime deployments. 

• Cloud & Infrastructure Proficiency: Hands-on experience deploying and managing applications on a major cloud platform (Azure preferred, AWS/GCP acceptable) using containerization (Docker) and orchestration (Kubernetes, Helm). 

• Production AI Application Experience: 2+ years of experience building applications that leverage large language models from providers like OpenAI, Anthropic, or Google Gemini. Direct experience with modern LLM patterns such as retrieval-augmented generation (RAG), hybrid search using vector databases (e.g., Pinecone, Elasticsearch), multi-agent AI systems with tool calls, and prompt engineering is required. 

• AI System Design and Evaluation: Experience designing and implementing robust evaluation frameworks for LLM-based systems, including rubric-based scoring, LLM Judges, or using tools like MLflow, alongside monitoring for performance and drift. 

• Large-Scale Data Processing: Familiarity with large-scale data processing platforms and tools (e.g., Databricks, Apache Spark). 

• Familiarity with the Modern AI Stack: Practical experience with libraries and frameworks like LangChain or LlamaIndex for building LLM-powered applications. 

• Leadership and Mentorship: Demonstrated ability to lead complex technical projects and foster the growth of other engineers. 

What We Offer:  

The annual base salary range for this position is $135,000 - $210,000. Additionally, this position is eligible for an annual discretionary bonus based on performance.

You will also be eligible for the following benefits: 

• Paid Time Off 

• Comprehensive benefits plan 
• Company RRSP Match 
• Development opportunities through the LinkedIn Learning platform 

About Guidepoint: 

Guidepoint is a leading research enablement platform designed to advance understanding and empower our clients’ decision-making process. Powered by innovative technology, real-time data, and hard-to-source expertise, we help our clients to turn answers into action. 

Backed by a network of nearly 1.75 million experts, and Guidepoint’s 1,600 employees worldwide, we inform leading organizations’ research by delivering on-demand intelligence and research on request. With Guidepoint, companies and investors can better navigate the abundance of information available today, making it both more useful and more powerful. 

At Guidepoint, our success relies on the diversity of our employees, advisors, and client base, which allows us to create connections that offer a wealth of perspectives. We are committed to upholding policies that contribute to an equitable and welcoming environment for our community, regardless of background, identity, or experience. 

#LI-SP1

#LI-Hybrid

About This Role

Caylent’s Anthropic Business Unit is a dedicated AI services practice built in partnership with Anthropic. 

The Forward Deployed AI Lead is the strategic and architectural lead on AI engagements. Paired with a Forward Deployed Engineer (FDE) who handles hands-on implementation, you own the engagement arc: shaping AI strategy, designing operating models, mapping AI outcomes to business value, and guiding executive stakeholders through adoption. You lead the room — the FDE builds what you architect.

This is a cross-functional role. You engage across lines of business, not just engineering, connecting AI initiatives to the outcomes that matter to each part of the organization. Every engagement is anchored to Anthropic’s platform and focused on real AI adoption outcomes.

Your clients span PE portfolio companies, growth-stage software businesses, and enterprise organizations. You are the strategic face of Caylent from kickoff through handoff.

What You’ll Do

Strategy and Architecture

• Own AI engagements end-to-end as the strategic lead, from discovery through executive handoff, partnered with an FDE who drives implementation
• Run structured discovery across engineering, product, and business stakeholders to map organizational context, AI readiness, and strategic goals across lines of business
• Design AI operating models that define how the organization adopts, governs, and scales AI. Not just within engineering, but across the business
• Define AI outcome maps that tie initiatives to measurable business results: efficiency gains, revenue impact, risk reduction, and time-to-value
• Lead AI maturity assessments and architect near-term and long-term adoption roadmaps aligned to Anthropic’s platform capabilities
• Facilitate executive workshops and enablement sessions for audiences ranging from engineering teams to C-suite leaders
• Deliver executive presentations to CTOs, VPs of Engineering, and line-of-business leaders covering current-state findings, ROI projections, and strategic recommendations
• Direct FDE work on Claude Code tooling, prompt architecture, and workflow automation. You set the technical direction, the FDE executes

Client Relationship and Business Development

• Identify expansion opportunities across lines of business. AI strategy work naturally surfaces adjacent needs in departments beyond the initial engagement
• Shape follow-on scope throughout the engagement: by Week 1, you should have a working hypothesis for the next engagement; by the final on-site block, you present it
• Build executive relationships that position Caylent as a long-term AI strategy partner, not a one-time vendor
• Attend on-site for the final Catalyst block: readout, workshop, and executive presentation

Internal Contribution

• Contribute reusable strategy frameworks, delivery artifacts, and methodology improvements back into the practice at engagement close
• Lead AI strategy engagements spanning multiple teams, platforms, and business functions
• Collaborate with FDEs to refine the architect-engineer delivery model and improve handoff patterns

What We’re Looking For

Required

• 8+ years of software development or technical architecture experience across varied stacks, including hyperscaler environments
• 3+ years in engineering leadership, technical consulting, solutions architecture, or a combination
• Demonstrated ability to engage across lines of business. You can talk to a VP of Engineering about CI/CD and a COO about operational efficiency in the same week
• Experience designing or advising on AI operating models, technology adoption strategies, or digital transformation programs
• Hands-on familiarity with Claude Code or equivalent AI-assisted development tools — you don’t need to configure them daily, but you need to speak the language credibly and direct an FDE’s work
• Certified Claude Architect
• Experience running structured stakeholder interviews, discovery sessions, and facilitated workshops with both technical and business audiences
• Strong executive communication: writing and presenting to CTOs, VPs of Engineering, and line-of-business leaders
• Experience delivering professional services engagements, including scope management, deliverable ownership, and client advisory
• Working knowledge of CI/CD pipelines, DevOps practices, and modern software development workflows

Preferred

• Experience mapping AI initiatives to business outcomes (revenue, efficiency, risk, time-to-value) with executive-level ROI framing
• Familiarity with PE portfolio company environments and board-level communication
• Background in solutions architecture, platform engineering, or enterprise technology strategy
• Experience with LLM prompt engineering, agentic AI workflow design, or AI product development
• Direct experience with Claude Code’s extensibility model
• Familiarity with SDLC maturity frameworks or workforce analytics (DORA, DevEx)
• Experience designing and facilitating workshops for mixed audiences — engineers, product managers, and business stakeholders

Who Thrives Here

The Forward Deployed AI Lead who do well here are a specific profile:

• Sat in the seat. You’ve led engineering teams or technology strategy inside a product company and understand the pressures executives navigate when adopting AI. Clients can tell.
• Thinks across the business. You don’t stop at engineering. You see how AI impacts operations, product, and go-to-market — and you can have those conversations with the people who own them.
• Knows when to slow down. You surface risks before committing to an approach. When the client’s definition of the work is wrong, you say so.
• Closes the next engagement. The final week of a Catalyst is a conversion window. You treat it that way — and the cross-LOB relationships you’ve built give you multiple paths to expand.
• Makes the methodology better. Every engagement teaches you something. You feed it back into the practice rather than keeping it in your head.
• Earns trust at the executive level. You’re as comfortable presenting an AI operating model to a COO in the morning as reviewing prompt architecture with your FDE that afternoon.

This is a poor fit if you want someone else to handle the sales motion or prefer execution-only roles. You are accountable for both strategic delivery quality and account expansion.

Why This Team

• Ground floor of something real: this BU is early, well-resourced, and anchored to Anthropic. You're writing the playbook, not inheriting one
• Own the methodology: you are shaping how AI-DLC enablement gets delivered. Every engagement you run improves the one after it
• Proximity to the market: your clients are PE portcos, enterprise engineering orgs, and Anthropic-referred customers at the frontier of AI adoption
• Revenue upside: Forward Deployed AI Lead who drive account expansion earn on revenue generated, not just delivery margin
• AI-native by default: this team uses AI in how it works. Specification-First Engineering is how we move from prototype to production fast
• Outcomes, not hours: advancement tied to delivery performance and account growth, not utilization

Benefits

Base Salary Range: The expected base salary range for this position is CAD $215,000 - $235,000 per year, commensurate with experience and qualifications.

Additional Compensation Components: In addition to the base salary, the compensation package may include bonuses, commissions, equity, and other incentives. The specific components will vary depending on the role and individual and/or company performance.

Role Description

GTM TechOps owns the systems, data, and automation that power the full customer lifecycle, from first touch through renewal and expansion. This role sits within that ecosystem, with a focus on enabling our customer-facing GTM teams through AI-powered tools and workflows.

As a Product Manager, GTM Systems, you will define and drive how AI is applied across our GTM systems. This includes identifying high-impact use cases, evaluating and integrating first-party and third-party tools, and ensuring solutions work seamlessly within the broader GTM ecosystem.

You will partner closely with engineering, technical architects, design, analytics, operations, and enablement to turn business needs into production-ready solutions that improve how sales, marketing, and customer teams operate day to day.

You will own the product lifecycle from problem definition through execution and adoption, including rapid prototyping to explore and validate ideas. You will set priorities and make tradeoffs that balance speed with long-term system health. 

Success in this role requires strong product judgment, systems thinking, and a practical understanding of applied AI in operational environments.

Responsibilities

Shape and drive the AI roadmap and priorities for GTM systems

• Define how AI is applied across customer-facing GTM workflows
• Identify, compare, and prioritize the highest-impact opportunities across sales, marketing, and customer success
• Balance near-term impact with longer-term platform capabilities such as decisioning and orchestration

Define and operationalize AI-driven workflows

• Shape how systems determine and trigger next best actions across the customer lifecycle
• Define how customer context, priority, and signals inform decisions and automation
• Establish when actions are handled by AI versus human teams, and how those interactions are coordinated

Deliver AI-powered solutions end to end

• Translate GTM needs into scalable product requirements
• Use rapid prototyping to explore ideas and de-risk decisions early
• Lead development from problem definition through launch in partnership with engineering and technical architects
• Ensure solutions are embedded in core systems and usable in day-to-day workflows

Drive adoption and business impact

• Partner with operations and enablement to drive adoption and change how GTM teams operate
• Define success metrics and iterate based on performance and user feedback
• Collaborate with engineering, technical architects, design, analytics, operations, and enablement to align on priorities, tradeoffs, and execution

Requirements

• Demonstrated product management experience, preferably in SaaS or internal platforms
• Strong understanding of CRM and GTM systems such as Salesforce and adjacent tools
• Proven ability to set product direction, prioritize effectively, and drive execution across cross-functional teams
• Strong analytical skills, including defining metrics and making data-informed decisions
• Experience evaluating and integrating third-party tools alongside first-party development
• Familiarity with applying AI to business workflows such as automation, decisioning, or copilots
• Ability to operate with speed and make sound tradeoffs under ambiguity
• Clear communication skills and ability to align engineering, technical architects, analytics, operations, and enablement stakeholders

Preferred Qualifications

• Experience with AI/automation in GTM workflows (agent assist, enrichment, copilots, etc.)
• Experience working in hybrid PLG and sales-led environments
• Experience with tools for experimentation, analytics, or workflow automation
• Experience driving simplification or consolidation across a fragmented tool or system landscape
• Experience leveraging AI/LLM-powered tools and workflows to improve product experiences, accelerate experimentation/analysis, and inform product decision-making (e.g., prototyping, AI-assisted analytics/insight generation)

Role Description

GTM TechOps owns the systems, data, and automation that power the full customer lifecycle, from first touch through renewal and expansion. This role sits within that ecosystem, with a focus on enabling our customer-facing GTM teams through AI-powered tools and workflows.

As a Product Manager, GTM Systems, you will define and drive how AI is applied across our GTM systems. This includes identifying high-impact use cases, evaluating and integrating first-party and third-party tools, and ensuring solutions work seamlessly within the broader GTM ecosystem.

You will partner closely with engineering, technical architects, design, analytics, operations, and enablement to turn business needs into production-ready solutions that improve how sales, marketing, and customer teams operate day to day.

You will own the product lifecycle from problem definition through execution and adoption, including rapid prototyping to explore and validate ideas. You will set priorities and make tradeoffs that balance speed with long-term system health. 

Success in this role requires strong product judgment, systems thinking, and a practical understanding of applied AI in operational environments.

Responsibilities

Shape and drive the AI roadmap and priorities for GTM systems

• Define how AI is applied across customer-facing GTM workflows
• Identify, compare, and prioritize the highest-impact opportunities across sales, marketing, and customer success
• Balance near-term impact with longer-term platform capabilities such as decisioning and orchestration

Define and operationalize AI-driven workflows

• Shape how systems determine and trigger next best actions across the customer lifecycle
• Define how customer context, priority, and signals inform decisions and automation
• Establish when actions are handled by AI versus human teams, and how those interactions are coordinated

Deliver AI-powered solutions end to end

• Translate GTM needs into scalable product requirements
• Use rapid prototyping to explore ideas and de-risk decisions early
• Lead development from problem definition through launch in partnership with engineering and technical architects
• Ensure solutions are embedded in core systems and usable in day-to-day workflows

Drive adoption and business impact

• Partner with operations and enablement to drive adoption and change how GTM teams operate
• Define success metrics and iterate based on performance and user feedback
• Collaborate with engineering, technical architects, design, analytics, operations, and enablement to align on priorities, tradeoffs, and execution

Requirements

• Demonstrated product management experience, preferably in SaaS or internal platforms
• Strong understanding of CRM and GTM systems such as Salesforce and adjacent tools
• Proven ability to set product direction, prioritize effectively, and drive execution across cross-functional teams
• Strong analytical skills, including defining metrics and making data-informed decisions
• Experience evaluating and integrating third-party tools alongside first-party development
• Familiarity with applying AI to business workflows such as automation, decisioning, or copilots
• Ability to operate with speed and make sound tradeoffs under ambiguity
• Clear communication skills and ability to align engineering, technical architects, analytics, operations, and enablement stakeholders

Preferred Qualifications

• Experience with AI/automation in GTM workflows (agent assist, enrichment, copilots, etc.)
• Experience working in hybrid PLG and sales-led environments
• Experience with tools for experimentation, analytics, or workflow automation
• Experience driving simplification or consolidation across a fragmented tool or system landscape
• Experience leveraging AI/LLM-powered tools and workflows to improve product experiences, accelerate experimentation/analysis, and inform product decision-making (e.g., prototyping, AI-assisted analytics/insight generation).

Compensation

Role Description

As a Senior Machine Learning Engineer, you will play a key role in advancing Dropbox’s mission to create a more enlightened way of working. Leveraging cutting-edge AI/ML technologies, you will design, build, deploy, and refine highly reliable AI agents operating at massive scale. Your work will power Dropbox Dash’s universal agentic search and autonomous organization features, transforming how millions of users collaborate, stay organized, and focus on the work that truly matters

Responsibilities

• Design and productionize agentic AI frameworks — including multi-agent coordination, planning, tool-use, and memory — that allow agents to maintain long-term context and execute complex tasks across the Dropbox ecosystem.
• Lead the end-to-end design of ML systems, from fine-tuning (SFT, RLAIF) and advanced prompting to inference optimization and production monitoring.
• Establish rigorous safety, alignment, and evaluation frameworks to ensure our autonomous systems are helpful, honest, and harmless.
• Collaborate across Product, Design, Infra, and Frontend teams to translate ambiguous user needs into concrete AI capabilities that move the needle for the business.
• Mentor junior engineers and serve as a core contributor to the broader Dropbox AI strategy, fostering a culture of technical excellence.

Many teams at Dropbox run Services with on-call rotations, which entails being available for calls during both core and non-core business hours. If a team has an on-call rotation, all engineers on the team are expected to participate in the rotation as part of their employment. Applicants are encouraged to ask for more details of the rotations to which the applicant is applying.

Requirements

• BS, MS, or PhD in Computer Science, Mathematics, Statistics, or a related quantitative field (or equivalent work experience).
• 8+ years of software engineering experience, with at least 5+ years dedicated to building and deploying production-scale AI/ML systems.
• Professional experience in ML modeling for complex systems such as Search, Ranking, or Recommender Systems.
• Deep familiarity with LLM architectures and hands-on experience with ML libraries (e.g., PyTorch, JAX, or similar).
• Strong proficiency in Python (required) and experience with systems languages like Go or C/C++. You should be comfortable building the infrastructure that surrounds the model.
• Extensive experience working with large-scale distributed data systems and high-throughput production environments.
• Exceptional analytical skills and a "bias to action" when navigating ambiguous technical challenges.

Preferred Qualifications

• PhD with a focus on Deep Learning, NLP, or Reinforcement Learning (RLHF/RLAIF).
• Proven track record of taking AI products from concept to launch, either at a massive scale (millions of users) or by leading multiple 0 → 1 cycles in a fast-paced environment.
• Hands-on experience with autonomous agent frameworks, multi-step planning, tool-use (function calling), and advanced RAG.
• Experience with inference optimization, model distillation, or fine-tuning techniques to improve performance and cost-efficiency.

Compensation

Role Description

Responsibilities

• BS, MS, or PhD in Computer Science, Mathematics, Statistics, or a related quantitative field (or equivalent work experience).
• 8+ years of software engineering experience, with at least 5+ years dedicated to building and deploying production-scale AI/ML systems.
• Professional experience in ML modeling for complex systems such as Search, Ranking, or Recommender Systems.
• Deep familiarity with LLM architectures and hands-on experience with ML libraries (e.g., PyTorch, JAX, or similar).
• Strong proficiency in Python (required) and experience with systems languages like Go or C/C++. You should be comfortable building the infrastructure that surrounds the model.
• Extensive experience working with large-scale distributed data systems and high-throughput production environments.
• Exceptional analytical skills and a "bias to action" when navigating ambiguous technical challenges.

Many teams at Dropbox run Services with on-call rotations, which entails being available for calls during both core and non-core business hours. If a team has an on-call rotation, all engineers on the team are expected to participate in the rotation as part of their employment. Applicants are encouraged to ask for more details of the rotations to which the applicant is applying.

Requirements

• BS, MS, or PhD in Computer Science, Mathematics, Statistics, or a related quantitative field (or equivalent work experience).
• 8+ years of software engineering experience, with at least 5+ years dedicated to building and deploying production-scale AI/ML systems.
• Professional experience in ML modeling for complex systems such as Search, Ranking, or Recommender Systems.
• Deep familiarity with LLM architectures and hands-on experience with ML libraries (e.g., PyTorch, JAX, or similar).
• Strong proficiency in Python (required) and experience with systems languages like Go or C/C++. You should be comfortable building the infrastructure that surrounds the model.
• Extensive experience working with large-scale distributed data systems and high-throughput production environments.
• Exceptional analytical skills and a "bias to action" when navigating ambiguous technical challenges.

Preferred Qualifications

• PhD with a focus on Deep Learning, NLP, or Reinforcement Learning (RLHF/RLAIF).
• Proven track record of taking AI products from concept to launch, either at a massive scale (millions of users) or by leading multiple 0 → 1 cycles in a fast-paced environment.
• Hands-on experience with autonomous agent frameworks, multi-step planning, tool-use (function calling), and advanced RAG.
• Experience with inference optimization, model distillation, or fine-tuning techniques to improve performance and cost-efficiency.

Compensation

Role Description

Dropbox, we believe in simplifying the way people work together. We provide a range of innovative cloud-based solutions to empower individuals and businesses to share, access, and collaborate on their files seamlessly. Staff Engineers are pivotal in shaping our mission of building a more enlightened way of working where everyone can unleash their creative potential without constraints.

This role owns large, ambiguous problem spaces directly tied to company metrics and translates them into a clear six-month technical roadmap, leading delivery for 15–20 engineers across team boundaries. The leader collaborates on ideas that shape area-level decisions, communicates effectively at all levels, and continuously integrates evolving business context into product and platform direction. They set and model high standards for engineering and operational excellence—driving reliability, scalability, execution rigor, and long-term maintainability across foundational systems—while remaining deeply hands-on through daily coding, design authorship, critical reviews, and architectural leadership. The role influences Core Engineering roadmaps, establishes technical direction, and brings strong instincts for high-quality consumer-facing experiences. They mentor senior talent, raising the technical bar through coaching and example, and extend their impact through org-level technical leadership. Over time, this leader grows from a cross-team technical driver into an org-level technical strategist, optimizing for the company as a whole rather than a single scope.

This team will own project Optimize Activation and Engagement Flows for Team Users. Lead a multi-year plan to modernize onboarding and activation, clean up core Dropbox surfaces, and build intelligent, adaptive systems that boost team activation, invites, and long-term engagement across platforms. Opportunity for large impact on the business helping Teams users activate on the right features to drive down churn. 

Our Engineering Career Framework is viewable by anyone outside the company and describes what’s expected for our engineers at each of our career levels. Check out our blog post on this topic and more here.

Responsibilities

• Lead the technical delivery of a team of 12 engineers to deliver high-impact business and customer outcomes.
• Shape technical direction and partner with Product Management as the DRI for critical company-wide objectives.
• Own massive, ambiguous technical and product problems that create company-wide opportunity.
• Be a prolific, hands-on coder who owns and implements the most critical, complex, and foundational components of the system.
• Influence roadmaps across orgs, breaking silos and steering decisions that change how Dropbox builds.
• Architect foundational systems that enable new product capabilities and operate reliably at the scale of hundreds of millions of users.
• Demonstrate senior technical leadership and maintain high engineering standards in a virtual-first environment.

Many teams at Dropbox run Services with on-call rotations, which entails being available for calls during both core and non-core business hours. If a team has an on-call rotation, all engineers on the team are expected to participate in the rotation as part of their employment. Applicants are encouraged to ask for more details of the rotations to which the applicant is applying.

Requirements

• BS, MS, or PhD in Computer Science or a related technical field involving coding (e.g., physics or mathematics) or equivalent technical experience
• Minimum of 12 years of experience as a software engineer 
• Must have worked in a consumer user-facing team (versus a platform team, a developer-facing API-based product, etc) 
• Must have a strong mix of skills and depth across multiple areas, including three or more of frontend, mobile, search, databases, storage, concurrency, and modern ML and LLM-based APIs and agentic frameworks

Role Description

Dropbox, we believe in simplifying the way people work together. We provide a range of innovative cloud-based solutions to empower individuals and businesses to share, access, and collaborate on their files seamlessly. Staff Engineers are pivotal in shaping our mission of building a more enlightened way of working where everyone can unleash their creative potential without constraints.

This role owns large, ambiguous problem spaces directly tied to company metrics and translates them into a clear six-month technical roadmap, leading delivery for 15–20 engineers across team boundaries. The leader collaborates on ideas that shape area-level decisions, communicates effectively at all levels, and continuously integrates evolving business context into product and platform direction. They set and model high standards for engineering and operational excellence—driving reliability, scalability, execution rigor, and long-term maintainability across foundational systems—while remaining deeply hands-on through daily coding, design authorship, critical reviews, and architectural leadership. The role influences Core Engineering roadmaps, establishes technical direction, and brings strong instincts for high-quality consumer-facing experiences. They mentor senior talent, raising the technical bar through coaching and example, and extend their impact through org-level technical leadership. Over time, this leader grows from a cross-team technical driver into an org-level technical strategist, optimizing for the company as a whole rather than a single scope.

This team will own project Optimize Activation and Engagement Flows for Team Users. Lead a multi-year plan to modernize onboarding and activation, clean up core Dropbox surfaces, and build intelligent, adaptive systems that boost team activation, invites, and long-term engagement across platforms. Opportunity for large impact on the business helping Teams users activate on the right features to drive down churn. 

Our Engineering Career Framework is viewable by anyone outside the company and describes what’s expected for our engineers at each of our career levels. Check out our blog post on this topic and more here.

Responsibilities

• Lead the technical delivery of a team of 12 engineers to deliver high-impact business and customer outcomes.
• Shape technical direction and partner with Product Management as the DRI for critical company-wide objectives.
• Own massive, ambiguous technical and product problems that create company-wide opportunity.
• Be a prolific, hands-on coder who owns and implements the most critical, complex, and foundational components of the system.
• Influence roadmaps across orgs, breaking silos and steering decisions that change how Dropbox builds.
• Architect foundational systems that enable new product capabilities and operate reliably at the scale of hundreds of millions of users.
• Demonstrate senior technical leadership and maintain high engineering standards in a virtual-first environment.

Many teams at Dropbox run Services with on-call rotations, which entails being available for calls during both core and non-core business hours. If a team has an on-call rotation, all engineers on the team are expected to participate in the rotation as part of their employment. Applicants are encouraged to ask for more details of the rotations to which the applicant is applying.

Requirements

• BS, MS, or PhD in Computer Science or a related technical field involving coding (e.g., physics or mathematics) or equivalent technical experience
• Minimum of 12 years of experience as a software engineer 
• Must have worked in a consumer user-facing team (versus a platform team, a developer-facing API-based product, etc) 
• Must have a strong mix of skills and depth across multiple areas, including three or more of frontend, mobile, search, databases, storage, concurrency, and modern ML and LLM-based APIs and agentic frameworks

Role Description

As a Principal Engineer at Dropbox, you will own company critical, loosely defined technical problems with multi year impact, operating at the intersection of technology, product, business strategy, and applied AI. You will define long term technical direction for customer facing experiences used by millions, identifying where AI meaningfully improves customer value and translating evolving business context and industry advances into durable, multi area strategies and roadmaps that shape how Dropbox builds, scales, and innovates, while remaining hands on in software development where it provides the greatest leverage.

Your influence will span organizations, setting foundational architecture, driving execution standards, and aligning senior technical and product leaders across boundaries. You will lead the responsible introduction and adoption of AI across product capabilities and engineering workflows, bring clarity to the most complex decisions, institutionalize engineering excellence, and contribute directly through critical design, prototyping, and code reviews.

In return, you will operate as a trusted technical partner to senior leadership, shape systems and platforms including AI powered foundations that define Dropbox’s future, and act as a company level technical strategist, advancing Dropbox’s mission to create a more enlightened way of working.

Our Engineering Career Framework is viewable by anyone outside the company and describes what’s expected for our engineers at each of our career levels. Check out our blog post on this topic and more here.

Responsibilities

• Own and drive technical outcomes across multiple teams and organizations, delivering company critical customer and business impact at scale.
• Define long term technical strategy and partner with senior Product and Engineering leaders as the technical owner for the most important company objectives.
• Tackle the most ambiguous and far reaching technical and product problems, shaping what the company builds as much as how it builds it.
• Remain deeply hands on in software development, owning and implementing the most critical, complex, and foundational parts of the system where leverage is highest.
• Influence and align roadmaps across organizations, resolving structural bottlenecks and changing how Dropbox builds and operates.
• Architect and evolve foundational systems (this may involve both frontend and backend systems) and platforms that enable new product capabilities and operate reliably at the scale of hundreds of millions of users.
• Model exceptional technical judgment and execution rigor, setting and sustaining high engineering standards across a distributed, virtual environment
• Drive AI adoption both to increase productivity and to produce AI based features.

Requirements

• Advanced degree in Computer Science or a related technical field involving substantial software development, or equivalent industry experience demonstrating deep technical mastery.
• 15+ years of experience designing, building, and evolving large scale software systems with sustained impact across multiple teams or organizations.
• Demonstrated success operating at a Principal level, owning company critical technical problems and influencing long term technical direction.
• Strong experience building consumer facing products at scale, with a deep understanding of user experience, performance, reliability, and operational excellence.
• Broad and deep technical expertise across multiple domains, including several of frontend, mobile, search, databases, storage systems, concurrency, and distributed systems.
• Practical experience applying modern ML, LLM based APIs, and agentic frameworks in production systems, with sound judgment around quality, cost, and risk.
• Ability to communicate complex technical concepts clearly and persuasively to senior engineering, product, and executive audiences.

Preferred Qualifications

• Experience defining and scaling company wide platforms or architectural standards that are adopted across multiple organizations.
• Proven track record of leading the introduction of new technologies such as AI or ML into core products or engineering workflows with durable impact.
• Experience operating in highly distributed, virtual first engineering organizations at global scale.

Compensation

Role Description

As a Principal Engineer at Dropbox, you will own company critical, loosely defined technical problems with multi year impact, operating at the intersection of technology, product, business strategy, and applied AI. You will define long term technical direction for customer facing experiences used by millions, identifying where AI meaningfully improves customer value and translating evolving business context and industry advances into durable, multi area strategies and roadmaps that shape how Dropbox builds, scales, and innovates, while remaining hands on in software development where it provides the greatest leverage.

Your influence will span organizations, setting foundational architecture, driving execution standards, and aligning senior technical and product leaders across boundaries. You will lead the responsible introduction and adoption of AI across product capabilities and engineering workflows, bring clarity to the most complex decisions, institutionalize engineering excellence, and contribute directly through critical design, prototyping, and code reviews.

In return, you will operate as a trusted technical partner to senior leadership, shape systems and platforms including AI powered foundations that define Dropbox’s future, and act as a company level technical strategist, advancing Dropbox’s mission to create a more enlightened way of working.

Our Engineering Career Framework is viewable by anyone outside the company and describes what’s expected for our engineers at each of our career levels. Check out our blog post on this topic and more here.

Responsibilities

• Own and drive technical outcomes across multiple teams and organizations, delivering company critical customer and business impact at scale.
• Define long term technical strategy and partner with senior Product and Engineering leaders as the technical owner for the most important company objectives.
• Tackle the most ambiguous and far reaching technical and product problems, shaping what the company builds as much as how it builds it.
• Remain deeply hands on in software development, owning and implementing the most critical, complex, and foundational parts of the system where leverage is highest.
• Influence and align roadmaps across organizations, resolving structural bottlenecks and changing how Dropbox builds and operates.
• Architect and evolve foundational systems (this may involve both frontend and backend systems) and platforms that enable new product capabilities and operate reliably at the scale of hundreds of millions of users.
• Model exceptional technical judgment and execution rigor, setting and sustaining high engineering standards across a distributed, virtual environment
• Drive AI adoption both to increase productivity and to produce AI based features.

Requirements

• Advanced degree in Computer Science or a related technical field involving substantial software development, or equivalent industry experience demonstrating deep technical mastery.
• 15+ years of experience designing, building, and evolving large scale software systems with sustained impact across multiple teams or organizations.
• Demonstrated success operating at a Principal level, owning company critical technical problems and influencing long term technical direction.
• Strong experience building consumer facing products at scale, with a deep understanding of user experience, performance, reliability, and operational excellence.
• Broad and deep technical expertise across multiple domains, including several of frontend, mobile, search, databases, storage systems, concurrency, and distributed systems.
• Practical experience applying modern ML, LLM based APIs, and agentic frameworks in production systems, with sound judgment around quality, cost, and risk.
• Ability to communicate complex technical concepts clearly and persuasively to senior engineering, product, and executive audiences.

Preferred Qualifications

• Experience defining and scaling company wide platforms or architectural standards that are adopted across multiple organizations.
• Proven track record of leading the introduction of new technologies such as AI or ML into core products or engineering workflows with durable impact.
• Experience operating in highly distributed, virtual first engineering organizations at global scale.

Compensation

About the team + role

We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards. 

The Vulnerability Management team’s mission is to reimagine security as an engineering and design challenge by building scalable, automated defense systems that proactively identify and reduce risk. The team is driving a shift toward an intelligence-driven defense model, leveraging advanced technologies like AI and machine learning to move beyond traditional “scan-and-patch” approaches and make security seamless for developers.

As a Senior Vulnerability Management Engineer, you will lead the transformation of vulnerability management into a self-scaling security platform. You’ll architect next-generation automated defense systems, using Agentic AI and machine learning to continuously discover, prioritize, and remediate risk at scale—helping make security efficient, proactive, and embedded into the development lifecycle.

This role is based in our Toronto, Canada office(s), with in-person attendance expected at least 3 days per week. 

At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office experience is intentional, energizing, and designed to fully support high-performing teams.

What you’ll do

• Set Strategic RBVM Vision: Act as the technical lighthouse, defining the multi-year roadmap and driving the move toward Risk-Based Vulnerability Management (RBVM), prioritizing vulnerabilities based on real-world exploitability and business context.
• Architect Agentic AI Systems: Design and deploy AI agents that autonomously triage findings, correlate threat intelligence, and generate production-ready remediations (e.g., automated Pull Requests for dependency updates and config drift).
• Build Exposure Intelligence: Develop systems that correlate vulnerabilities with runtime context and infrastructure topology (Kubernetes/AWS) to accurately model real-world blast radius and ensure engineers only fix what is actually exploitable.
• Automate Triage & Self-Healing: Create "paved roads" and CI/CD guardrails that prevent specific vulnerability categories from ever reaching production, reducing manual toil for the entire engineering organization.
• Data-Centric Visibility: Build high-fidelity dashboards using LLM-powered summarization to translate complex security signals into actionable insights for engineering leadership.
• Lead Emergency Response: Orchestrate the technical response to high-impact zero-days by rapidly performing cross-environment blast-radius analysis.
• Drive Execution Ownership: Take full ownership of operational security work, ensuring that critical vulnerabilities are systematically eradicated while maintaining high engineering velocity.

What you bring

• Experience: 5+ years in Security Engineering with a track record of leading high-impact automation or security platform initiatives at a Senior or Staff level.
• AI & Agentic System Fluency: Hands-on experience building or deploying agentic systems or LLM orchestration frameworks (e.g., LangChain, AutoGPT) to solve complex security or engineering problems at scale.
• Bug Bounty & Exploit Proficiency: Active experience participating in or managing Bug Bounty programs; a deep understanding of how attackers exploit vulnerabilities and how to translate those findings into systemic fixes.
• Engineering Excellence: Strong software engineering background with proficiency in Go or Python and a history of building scalable, API-driven security tooling.
• Modern Infrastructure Depth: Deep knowledge of securing AWS and Kubernetes-based architectures.
• Vulnerability Domain Knowledge: High familiarity with vulnerability categories, exploitability, and modern risk frameworks (CVSS, EPSS, CISA KEV).
• Detection Ecosystems: Experience with modern platforms like Snyk, Semgrep, Wiz, EndorLabs, or TruffleHog.
• Velocity Mindset: A commitment to reducing security friction and a track record of working effectively with high-velocity engineering teams.

Nice to have

• Fintech Experience: Experience navigating security in highly regulated or high-growth financial environments.
• Security as Code: Experience implementing "Security as Code" within large-scale CI/CD environments.

What we offer

• Challenging, high-impact work to grow your career
• Performance driven compensation with multipliers for outsized impact, bonus programs, and equity ownership
• Top tier benefits to fuel your work, including supplemental health insurance, ancillary insurance, and mental health support programs
• Lifestyle wallet - a highly flexible employer-paid benefits spending account expenses beyond traditional benefits such as wellness, childcare, learning, and more.
• Time off to recharge including company holidays, paid time off, sick time, paid volunteer time off, parental leave, and more!
• Exceptional office experience with catered meals, events, and comfortable workspaces. 
• Monthly commuter stipend to help offset in-office commuting costs

Our team is committed to providing an inclusive and welcoming interview experience for all candidates. If you require a specific accommodation during the application or interview process due to a physical or mental condition, please complete this Applicant Accommodation Form to notify our team. The form should only be completed if you need a specific accommodation.

AI Usage Disclosure: Robinhood uses artificial intelligence (AI) tools to support parts of our recruiting process. These tools enhance the efficiency and consistency of our hiring process; however, all hiring decisions are made by our hiring teams.

Vacancy Notice: This job posting represents an existing vacancy that we are actively seeking to fill.

About the team + role

We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards. 

At Robinhood, we view security as an engineering and design challenge, not an administrative one. We are looking for a lead architect for our next-generation automated defense systems. As a Senior Vulnerability Management Engineer, you will transform the program into a self-scaling security platform that transcends traditional "scan-and-patch" cycles. You will lead the shift to an Intelligence-Driven Defense model by leveraging Agentic AI and Machine Learning to automate the discovery, prioritization, and remediation of risk at scale, ultimately making security "cheap" for our developers.

This role is based in our Menlo Park, CA office, with in-person attendance expected at least 3 days per week.

At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office experience is intentional, energizing, and designed to fully support high-performing teams. 

What you’ll do

• Set Strategic RBVM Vision: Act as the technical lighthouse, defining the multi-year roadmap and driving the move toward Risk-Based Vulnerability Management (RBVM), prioritizing vulnerabilities based on real-world exploitability and business context.
• Architect Agentic AI Systems: Design and deploy AI agents that autonomously triage findings, correlate threat intelligence, and generate production-ready remediations (e.g., automated Pull Requests for dependency updates and config drift).
• Build Exposure Intelligence: Develop systems that correlate vulnerabilities with runtime context and infrastructure topology (Kubernetes/AWS) to accurately model real-world blast radius and ensure engineers only fix what is actually exploitable.
• Automate Triage & Self-Healing: Create "paved roads" and CI/CD guardrails that prevent specific vulnerability categories from ever reaching production, reducing manual toil for the entire engineering organization.
• Data-Centric Visibility: Build high-fidelity dashboards using LLM-powered summarization to translate complex security signals into actionable insights for engineering leadership.
• Lead Emergency Response: Orchestrate the technical response to high-impact zero-days by rapidly performing cross-environment blast-radius analysis.
• Drive Execution Ownership: Take full ownership of operational security work, ensuring that critical vulnerabilities are systematically eradicated while maintaining high engineering velocity.

What you bring

• Experience: 5+ years in Security Engineering with a track record of leading high-impact automation or security platform initiatives at a Senior or Staff level.
• AI & Agentic System Fluency: Hands-on experience building or deploying agentic systems or LLM orchestration frameworks (e.g., LangChain, AutoGPT) to solve complex security or engineering problems at scale.
• Bug Bounty & Exploit Proficiency: Active experience participating in or managing Bug Bounty programs; a deep understanding of how attackers exploit vulnerabilities and how to translate those findings into systemic fixes.
• Engineering Excellence: Strong software engineering background with proficiency in Go or Python and a history of building scalable, API-driven security tooling.
• Modern Infrastructure Depth: Deep knowledge of securing AWS and Kubernetes-based architectures.
• Vulnerability Domain Knowledge: High familiarity with vulnerability categories, exploitability, and modern risk frameworks (CVSS, EPSS, CISA KEV).
• Detection Ecosystems: Experience with modern platforms like Snyk, Semgrep, Wiz, EndorLabs, or TruffleHog.
• Velocity Mindset: A commitment to reducing security friction and a track record of working effectively with high-velocity engineering teams.

Nice to have

• Fintech Experience: Experience navigating security in highly regulated or high-growth financial environments.
• Security as Code: Experience implementing "Security as Code" within large-scale CI/CD environments.

What we offer

• Challenging, high-impact work to grow your career.
• Performance-driven compensation with multipliers for outsized impact, bonus programs, equity ownership, and 401(k) matching.
• Best-in-class benefits to fuel your work, including 100% paid health insurance for employees with 90% coverage for dependents.
• Lifestyle wallet — a highly flexible benefits spending account for wellness, learning, and more.
• Employer-paid life & disability insurance, fertility benefits, and mental health benefits.
• Time off to recharge including company holidays, paid time off, sick time, parental leave, and more!
• Exceptional office experience with catered meals, events, and comfortable workspaces.