About the Team:

We’re looking for a Staff Software Engineer I/II to join our Data Ingestion Team, which builds and operates the critical infrastructure that serves as the “front door” of StackAdapt’s event flow. In this role, you’ll own technical direction for critical parts of our ingestion platform, lead large-scale initiatives, and shape how data flows across the company.

The Data Ingestion team tackles complex distributed systems challenges at massive scale, with a focus on scalability, performance, and reliability. Our systems process over 10 billion events per day, powering core functions across bidding, reporting, billing, analytics, and machine learning. You will work on challenging technical problems and partner with teams across the company to drive key initiatives.

We design + build low-latency, highly reliable distributed systems for impressions, clicks, conversions, and third-party signals, ensuring data is accurate and available to downstream teams in real time. This is a high-impact area at the core of StackAdapt’s platform, the systems you own will directly shape data quality, system reliability, and the speed at which teams across the company can build and innovate. Our work sits at the cutting edge of large-scale distributed systems, leveraging modern technologies and architectures to solve complex real-time data challenges. The core stack includes Golang, Kafka, TiDB, Aerospike, Vitess, Kubernetes, and more.

If you enjoy solving complex distributed systems problems at scale and driving technical impact across teams, this role would be a great fit for you.

StackAdapt is a Remote First company. We are open to candidates located anywhere in Canada or the United States for this position.

What You’ll Be Doing:

• Own and lead large technical initiatives end-to-end, from design through production and monitoring
• Provide technical leadership and mentorship to engineers across the team
• Design, build, and operate highly scalable, distributed ingestion services for real-time and near-real-time scenarios
• Contribute hands-on as needed while enabling the team to execute effectively
• Build and maintain event ingestion pipelines using streaming technologies like Kafka
• Work with high-volume storage systems and databases to persist and serve data efficiently
• Partner with Data, ML, Product, and Platform teams to support evolving requirements
• Improve code quality, testing practices, system reliability, and observability
• Participate in design reviews, code reviews, and architectural discussions
• Balance and prioritize projects to maximize impact and align with company objectives

What You’ll Bring to the Table:

• Extensive experience building distributed systems and high-throughput backend services
• Proven ability to lead technical direction and drive large, cross-team initiatives
• Strong problem-solving and communication skills, with comfort working in ambiguous, complex domains
• Collaborative mindset with the ability to influence across teams
• Ability to think strategically, lead technically, and drive high-impact, scalable solutions
• Hands-on experience with streaming systems (Kafka or similar)
• Strong understanding of distributed systems trade-offs (consistency, availability, partition tolerance, scalability)
• Maintains an AI-forward approach to software engineering - leveraging AI to boost productivity, collaboration, and business automation
• Bonus: Familiarity with AdTech, event-driven architectures, or analytics systems

#LI-TM8

Engineering at Brex

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

As a Security Operations Engineer at Brex, you will focus on preventing, detecting and responding to security threats across Brex's corporate and cloud environments. You will use existing systems and develop tools to improve our security capabilities. Our team is responsible for functions across corporate security, detection & response and infrastructure security domains; and we perform systems engineering and automation to support those functions. 

Security Operations is part of our wider Trust & IT organization which means you will have the opportunity to work closely with Application Security, Corporate Engineering, GRC and IT and to improve security configurations, drive positive employee behaviors and generally work to prevent events from becoming incidents. You will also help build and maintain our team’s open source project Substation and have the opportunity to contribute to the Brex Tech Blog. You’ll be part of a team that actively contributes to the wider security community and has a commitment to mentorship and engineering excellence.

We’re looking for individuals with a strong background and interest in detecting, responding to, and resolving security incidents and security challenges. You should be comfortable dealing with lots of moving pieces, changing priorities, and new technologies, while having a keen eye for detail. Most importantly, you should be enthusiastic about working with a variety of backgrounds, roles, and people across Brex. Building a world-class financial service requires world-class security.

Where you’ll work

This role will be based in our San Francisco 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

• Work on a highly cross-functional team to prevent, detect and respond to security threats across Brex's corporate and cloud environments
• Perform security incident response, investigation, remediation, and documentation, participate in periodic threat hunting and security exercises
• Leading, scoping and building features, participate in designing, and maintaining tools and systems which support the team’s domains – corporate security, detection & response and infrastructure security 
• Collaborating and partnering with engineering and operations teams to drive remediation of security issues, while balancing prioritization of those security issues within SLA and teams’ respective backlogs
• Caring about secure system design, valuing building things correctly, an understanding of a MVP approach and an empathetic mindset when working with others

Requirements

• Bachelor’s degree in Computer Science, Engineering or related field OR equivalent training / fellowship OR 5+ years work experienceExperience working in a corporate security, detection & response or infrastructure security role with responsibilities for security alert triage and security incident response 
• Familiarity with CI/CD systems and DevOps workflows (e.g. Buildkite, Flux, Git, Terraform) in cloud environments (e.g. AWS, Azure, GCP)
• Experience with deploying and maintaining some of the security services and tools owned by the team (e.g. - SIEM, data pipelines, SOAR, domain monitoring, endpoint tooling, email protection tooling, cloud security tools)
• While not primarily a development role, the team develops and maintains tools written in Go and Python, so experience with coding is required
• You thrive in a collaborative environment filled with a diverse group of people with different expertise and backgrounds. We currently have around 30 nationalities represented with more than ½ the company working in a country different from the one they grew up in.

Bonus points

• Proficiency with Go and other programming languages 
• Experience with securing distributed systems in AWS, cloud and Kubernetes environments
• Contributions to the wider technical community (open source, public research, mentorship, community organizing, blogging, presentations, etc)

Compensation

The expected salary range for this role is $192,000 - $240,000. 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.

Marqeta is looking for a talented Senior Software Engineer to independently identify and deliver software solutions on our Data Infrastructure team through a set of milestones spanning a specific platform focus or a multi-component system. You will own and deliver projects in service of quarterly goals on the team and independently identify solutions to solve ambiguous, open-ended problems. You will work in collaboration with your team and cross-functional partners.

The Data Infrastructure team, within our Data & ML Platforms organization, is responsible for the data lakehouse, streaming, orchestration, and catalog platforms that power analytics and AI across Marqeta. We're a platform engineering team building infrastructure that other engineering teams depend on.

At Marqeta, participation in a rotational on-call pager duty is a required part of the software engineering role. The specifics of the rotation may vary by team, depending on team size and structure, and will be discussed further during the interview process.

We work Flexible First. This role can be performed remotely anywhere within Ontario or British Columbia, Canada. We’d love for you to join us!

Learn more about our Product and Engineering team

The Impact You'll Have

• Define and deliver well-scoped milestones for projects, and may be a technical lead for projects on your team.
• Lead design for small-to-medium components and participate in design for larger components, moving from task-level impact to small-to-medium project-level impact.
• Have significant ownership of a component of the data infrastructure, including its reliability, performance, and developer experience.
• Identify gaps and propose plans towards addressing those gaps.
• Independently write code that is clear, well-tested, and appropriately flexible, reusable, and adaptable to changing requirements.
• Actively level up less-experienced members of your team by helping them with their craft, providing guidance, and setting a good example.
• Participate in on-call coverage.

Who You Are

• 5+ years of experience as a software engineer with a Bachelor's degree; or 3 years of experience with an advanced degree. In lieu of a degree, 8+ years of relevant experience may suffice.
• Strong proficiency in Python in a production context.
• Proficiency with SQL.
• Experience working with distributed systems.
• Production experience with multiple core data technologies, including Apache Kafka, Apache Spark, and Apache Airflow (or close equivalents).
• Production experience with modern table formats (Parquet, Hudi, Iceberg, or Delta Lake).
• Production experience with AWS or another major cloud.
• Experience with infrastructure-as-code (Terraform, CloudFormation, CDK, or equivalent).
• Experience monitoring and alerting on production systems.
• Ability to decompose business problems into solutions that may require designs with multiple interacting components.
• Ability to build correct, maintainable software components.
• Ability to work with cross-functional stakeholders to identify technical blindspots and clarify ambiguity.
• Ability to present clear and concise messages tailored to various audiences; able to communicate clearly and respectfully both verbally and in writing.
• A focus on quality and meeting deadlines.
• Ability to decompose business problems into solutions that may require designs with multiple interacting components.
• Ability to build correct, maintainable software components.
• Ability to work with cross-functional stakeholders to identify technical blindspots and clarify ambiguity.
• Ability to present clear and concise messages tailored to various audiences; able to communicate clearly and respectfully both verbally and in writing.
• A focus on quality and meeting deadlines.

Nice-To-Haves

• Experience with payments or the FinTech space.
• Experience with Apache Iceberg specifically.
• Experience with CDC tooling, particularly Debezium or Kafka Connect.
• Experience with data catalog tooling (DataHub or equivalent).
• Experience with Java in addition to Python.
• Exposure to Kubernetes and container-based workloads.
• Experience building scalable software platforms.

Our (typical) process:

1. Application Submission
2. Recruiter Video Call
3. Coding Interview & Hiring Manager Interview
4. Virtual “Onsite” consisting of three 60 minute rounds
5. Offer!

Compensation and Benefits

Marqeta is a Flex First company which allows you to choose your best working environment, whether that be from home or at a company office. To support Flex First, we calibrate pay to a competitive value according to working location. 

When determining salaries, we consider several factors including, but not limited to, skills, prior experience, and work location. The new-hire base salary range for this position, reflected in CAD, is: 116,000 - 145,000

We also believe in recognizing the contributions of our people. That's why we award annual bonuses to eligible employees, rewarding both individual performance and the success of the entire company.

Along with monetary compensation, Marqeta offers

• Multiple health insurance options
• Flexible vacation time
• Retirement savings program with company contribution
• Equity in a publicly-traded company 
• Monthly stipend to support our remote work model
• Annual “development dollars” to support our people growth and development
• Family-forming benefits and up to 20 weeks of Parental Leave

MongoDB Technical Services Engineers use their exceptional problem solving and customer service skills, along with their deep technical experience, to advise customers and to solve their complex MongoDB problems. Technical Service Engineers are experts in the entire MongoDB ecosystem - database server, drivers, cloud and infrastructure. This also includes services such as Atlas (database as a service), or Cloud Manager (which helps customers with automation, backup and monitoring of their MongoDB systems). Our engineers combine their MongoDB expertise with passion, initiative, teamwork and a great sense of humor to achieve exceptional results for our customers.

We are looking to speak to candidates who are based in Vancouver for our hybrid working model.

Cool things you’ll do

MongoDB is on a mission to change the way people think about databases. Along the way, our customers and partners encounter questions and issues about how our approach to databases works for their use case. In Technical Services, it's our job to help these people.

You'll be working alongside our largest customers and partners, solving their complex issues - resolving questions on architecture, performance, recovery, security, and everything in between.

You'll be an expert resource on standard methodologies in running MongoDB at scale, whatever that scale may be. You'll be an advocate for customers' and partners’ needs - working with our product management and development teams on their behalf. 

You'll contribute to internal projects, including software development of support tools for performance, benchmarking, and diagnostics. Externally, you will work with many of MongoDB's top ISV partners and ensure excellence for our joint customers. 

In addition, you will also be responsible for mentoring and ramping new team members and taking initiatives in building knowledge of new product lines within the MongoDB ecosystem.

What you need

We consider all candidates with an eye for those who are self taught, insatiably curious, and multi-faceted.

It’s important for candidates to check off these boxes:

• Systems engineering experience, including Linux performance, memory management, I/O tuning, configuration, security, networking, clusters, and troubleshooting
• Should have a good understanding of Networking concepts and protocols (DNS, TCP/IP, SSL/TLS, etc.)
• Experience managing large scale databases (e.g. RDBMS or NoSQL)
• Storage engineering experience, including NAS, SAN, SSD, multi-pathing, and caching
• Experience building and maintaining complex mission-critical production database systems
• Be able to read and write code, and basic coding/scripting ability in one or more languages: Java, Python, Ruby, C, C++, C#, Javascript, node.js, Go, etc.
• Experience working with APIs and other application integration technologies
• Broad awareness of customer workloads and use cases, including performance, availability, and scalability
• Experience analyzing issues holistically, from the application tier through the database, down to the storage
• Genuine desire to help people
• Ability to think on your feet, remain calm under pressure, and solve problems in real-time
• Desire and ability to rapidly learn a wide variety of new technical skills
• Collaboration: Ability to work collaboratively amongst cross functional teams (partner, sales, support, customer success, etc)
• Willingness and clarity of thoughts to be able to work in ambiguous multi-party situations where motivations and incentives are sometimes misaligned
• General understanding of partner ecosystems

Bonus Points

• Experience in one or more programming languages developing applications using a NoSQL or SQL database
• Strong understanding of authentication systems such as LDAP, Kerberos, AD
• Experience using or managing MongoDB
• Experience using distributed version control systems, and in particular git
• Experience using any cloud services stack such as AWS, Azure or GCP
• Experience with Kubernetes or other orchestration systems using vendor-specific Enterprise operators
• Experience in working software product teams, and familiarity with product release processes from planning to release
• Experience with one or more 3rd party partner technologies and software in the areas of security and fraud, big data analytics and AI, healthcare, content management, IoT, database performance monitoring and management; financial services, healthcare services, telco etc
• General understanding of the genAI concepts and technology companies in this space

Success Measures

• In 3 months, you’ll have gained a deep understanding of MongoDB and its partner ecosystem. You will complete New Hire Training
• In 6 months, you will be comfortable working frontline with our customers and partners. You will also complete the MongoDB Certified DBA Associate exam
• In 12 months, you will be a technical specialist within MongoDB and will be helping your peer engineers in advanced diagnostics. Also, you will be encouraged to handle technical escalations independently

About MongoDB

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform—the most widely available, globally distributed database on the market—helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and nearly 60,000 customers—including 75% of the Fortune 100 and AI-native startups—relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. 

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB is an equal opportunities employer.

Req ID: 4263346828

The Team

Platform Engineering is the department within SRE that is responsible for a range of critical infrastructure and operational functions that support the broader engineering organization. Among these are our multi-cloud-provider Kubernetes infrastructure, deployment machinery, and observability and alerting systems.

The Fabric team manages the infrastructure that enables secure communication between systems and from the public internet. Their responsibilities encompass network architecture, service mesh, and edge load balancing, ensuring customer data remains safe in transit. The team plays a crucial role in developing and maintaining the reliable and globally connected multi-cloud network that supports MongoDB products.

This role can sit in our Toronto or Vancouver offices, or fully remote from anywhere in North America. When based in an office, we provide hybrid work accommodation.

Role Overview

We are seeking a talented Site Reliability Engineer (SRE) with a strong networking background to join the Fabric team. This role is pivotal in building and maintaining the robust infrastructure necessary for secure and efficient communication between our services. As an SRE on the Fabric team, you will leverage your expertise in networking, distributed systems, and automation to ensure our systems are resilient, scalable, and reliable.

The ideal candidate should

• Have 10+ years of experience working on software and operating distributed systems, with deep expertise in networking fundamentals and a good understanding of how the internet works, e.g. TCP/IP (including IPv6), DNS, TLS/mTLS, BGP, tunnels, overlays, and SDN principles
• Possess a customer-focused mindset, driving improvements that benefit end-users
• Value efficiency in processes and operations, and display a strong preference for automation over manual processes (“allergic to ops work”)
• Be intimately familiar with modern cloud-based infrastructure and the network design primitives of at least one of AWS, Azure, or GCP, e.g. VPCs, subnetting, routing, VPNs, peering, private link / private service connect, and CDNs
• Have a strong knowledge of service mesh and load-balancing concepts, and be eager to implement these in a multi-cloud environment

Expectations

• Participate in the development of a reliable and resilient multi-cloud globally-connected network that is crucial for MongoDB’s services
• Collaborate with service-owning teams to provide internal support, addressing technical issues and offering guidance on best practices for service-to-service connectivity
• Participate in a 24/7 on-call rotation to swiftly resolve issues related to network architecture and service-to-service connectivity, ensuring minimal disruption and high availability

About MongoDB

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform, the most widely available, globally distributed database on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and over 60,000 customers, including 75% of the Fortune 100 and AI-native startups, relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. 

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB is an equal opportunities employer.

Req ID: 426185

About the Cloud Payments team

Cloud Payments is part of the Cloud Billing organization. As MongoDB’s Cloud business grows, the billing and payments stack becomes increasingly mission‑critical. Our team:

• Ingests and aggregates detailed metering and usage data from internal services and major cloud providers (AWS, Azure, GCP)
• Calculates and generates daily customer bills for millions of customers worldwide
• Integrates with payment processors and internal financial systems to support Finance, Sales, Marketing, and Accounting
• Continuously improves customer-facing billing and payments experiences and the reliability and scalability of our backend systems

We’re a group of engineers who care deeply about code quality, correctness, and observability, and who are comfortable collaborating with both highly technical partners and non-technical stakeholders across the business.

The role

We’re looking for a Software Engineer 3 to help design, build, and operate the services that power Cloud Payments. You’ll work primarily in the JVM ecosystem (Java and related tooling), with a focus on large-scale, distributed systems that have to be correct, resilient, and auditable.

This is a Canada-based, fully remote role. You’ll collaborate closely with teammates and stakeholders across North America time zones, including engineers in the broader Cloud Billing organization.

What you’ll do

In this role, you will:

• Design, implement, and operate backend services that ingest, process, and reconcile large volumes of usage and billing data from internal and external systems
• Collaborate with product, Finance, Revenue, and other engineering teams to evolve our billing and payments capabilities and improve customer experience
• Own features end‑to‑end: requirements, design, implementation, testing, rollout, monitoring, and iterative improvement
• Help scale and harden our systems as Atlas and our broader Cloud business continue to grow rapidly
• Participate in architecture discussions, technical design reviews, and code reviews to keep our systems robust and maintainable
• Contribute to improving our tooling, observability, and development workflows so the whole team can move faster and safer
• Take part in an on‑call rotation that treats reliability as a team sport, not an individual burden

What we’re looking for

You may be a great fit if you:

• Have 3+ years of experience building and maintaining backend systems in a compiled language, ideally Java
• Understand core object‑oriented design principles and how to apply them to complex, evolving systems
• Have experience with distributed systems and services that need to be highly available, observable, and correct at scale
• Are comfortable working with databases (relational and/or non‑relational such as MongoDB) in production environments
• Communicate clearly and enjoy working with both technical and non‑technical stakeholders across multiple teams
• Are curious, collaborative, and motivated by solving real customer and business problems rather than just closing tickets

Nice to have (but not required):

• Experience with billing, payments, or other financial systems where correctness, auditability, and compliance really matter
• Experience with cloud platforms (AWS, GCP, Azure) and modern communication protocols like gRPC
• Familiarity with data-intensive applications, data pipelines, or data lakes
• Exposure to working with I/O frameworks like Reactor
• Experience with containerization and orchestration (e.g., Docker, Kubernetes)
• Prior exposure to MongoDB as a developer or operator

We don’t expect you to check every box. If you’re excited about the space and think you could do great work here, we’d love to hear from you.

Working model & location

• Location: Canada
• Working model: Fully remote, with colleagues primarily across North American time zones

How we’ll support you

MongoDB is committed to building a supportive, inclusive, and growth‑oriented environment for everyone on the team. Our approach to benefits and working models is designed to support your physical, emotional, financial, and family well‑being, and to give you flexibility in how you do your best work.

You’ll have opportunities to:

• Work on complex, meaningful projects that directly impact MongoDB’s Cloud business
• Learn from and collaborate with experienced engineers across Cloud Billing and other parts of MongoDB
• Grow your career through mentorship, feedback, and stretch projects aligned with your interests

About MongoDB

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform, the most widely available, globally distributed database on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and over 60,000 customers, including 75% of the Fortune 100 and AI-native startups, relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. 

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB is an equal opportunities employer.

REQ ID: 1273389937

 #LI-Hybrid

Your role
As a Sr. Software Engineer on the Tel Core team, you are the steward of our media engine’s evolution. You will bridge the gap between high-level product goals and technical execution, ensuring our telephony stack remains resilient as we scale. You’ll mentor peers and shape the long-term roadmap while fostering a culture of engineering excellence. Your success is defined by the seamless, high-quality audio experience of millions of users.

This position reports to an Engineering Manager in the Telephony Core team and has the opportunity to be based in either Vancouver or Kitchener, Canada locations 

We don’t mind if you come from a different engineering background or haven’t worked in real-time media before. Just be excited to learn, to contribute to the team, and to build a fast, reliable, elegant product that delights our customers.

What you’ll do

• Maintain and modernize the real-time services that run on the Telephony Engines. Architect backend libraries and APIs to integrate with the broader Telephony Platform.
• Build and optimize low-latency media pipelines for voice and video—tuning codecs, RTP flows, and congestion-control behavior to deliver consistently clear conversations over unreliable networks.
• Investigate and resolve complex production issues across PSTN, WebRTC, and carrier boundaries using Telephony Engine logs, PCAPs, observability tools, and data-driven experimentation.
• Run load, failover, and regression tests on Telephony Engines and backend services to validate scalability, resilience, and capacity limits
• Partner with Tel Cloud, Tel Edge, Calling, and AI teams to design end-to-end call flows and integrations
• Participate in on-call and release rotations, owning Terraform- and GKE-backed rollouts, monitoring health, and driving follow-ups that continuously make the platform safer and easier to operate.
• Shape the Tel Core roadmap by turning broad epics into clear designs and mentoring other engineers.

Skills you’ll bring 

• Bachelor's degree in Computer Science or equivalent practical experience.
• 5+ years of software engineering experience, including owning substantial production backend systems in a SaaS or real‑time communications environment.
• Demonstrated proficiency in coding with AI agents to accelerate development and improve code quality.
• Deep expertise in C/C++ and Python.
• Experience with (or strong interest in learning) SIP, WebRTC, RTP/RTCP, DTLS/SRTP, and media codec negotiation in a production setting.
• Experience troubleshooting and improving real‑time media quality (e.g., jitter, packet loss, choppy audio, codec issues) is a strong plus.
• Comfortable working on KTLO (bugs, refactors, upgrades) as well as strategic roadmap items, and using data to prioritize impact.
• A deep understanding of reliability engineering, including the ability to build observability into services, eliminate performance bottlenecks, and manage the lifecycle of safe software releases.
• A strong sense of urgency, personal agency, and customer empathy.
• Passion for data driven decisions, building resilient systems, and solving classes of problems.

Our tech stack

• C, C++, Python, Go, Lua.
• Kubernetes, Redis, ElasticSearch, BigQuery.
• Google Cloud Platform: Cloud Run, GKE, Datastore, Pub/Sub.

The Payment Platform Team powers Asana’s subscription, billing, and payment infrastructure — the systems responsible for processing all revenue and enabling how we monetize the product. Our mission is to enable engineering teams to safely and rapidly build on billing capabilities, while empowering business teams to launch and iterate on pricing and packaging strategies.

Our work sits at the intersection of every major revenue lever at Asana — from incentives that drive user growth, to the product catalogue that defines how we package and sell, to the core billing systems through which every dollar of revenue flows. This gives the team a unique opportunity to directly influence both product strategy and business outcomes. Engineers on this team have the opportunity to shape architecture, reliability, and long-term scalability of revenue-critical systems.

This role is based in our Vancouver office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements.

What you’ll achieve

• Design, build, and maintain backend services using Scala and gRPC within a modern microservices architecture to support Asana’s global growth.
• Own features end-to-end, from initial problem definition and design to implementation, launch, and iteration.
  Lead large, cross-team initiatives from ambiguous problem spaces to execution, driving key architectural decisions for revenue-critical systems.
• Collaborate closely with cross-functional stakeholders in Product, Design, Finance, and partner engineering teams to deliver high-impact monetization solutions.
• Ensure systems are reliable, scalable, and performant, specifically focusing on evolving cell-based distributed architectures.
• Mentor fellow engineers and contribute to a high-performing technical culture by participating in design and code reviews.

About you

• Strong experience building and scaling backend or full-stack systems, ideally with distributed systems or complex data models.
• Proven ability to take full ownership of technical problems and drive them to resolution across the entire stack.
• Excellent collaboration skills with the ability to influence both engineering and non-engineering partners.
• Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making.
• Experience with (or a strong interest in) billing, payments, or financial systems and cloud infrastructure like Kubernetes.
  Thrives in an environment where you can evolve cell-based architectures, sharded systems, or multi-tenant distributed systems.

What we’ll offer

Our comprehensive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission. We believe that compensation should be reflective of the value you create relative to the market value of your role. To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit.

For this role, the estimated base salary range is between $176,000 - $200,000. The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. In addition to base salary, your compensation package may include additional components such as equity and benefits.

We strive to provide equitable and competitive benefits packages that support our employees worldwide and include:

• Mental health, wellness & fitness benefits
• Career coaching & support
• Inclusive family building benefits
• Long-term savings or retirement plans
• In-office culinary options to cater to your dietary preferences

#LI-Hybrid #LI-HC1

THE ROLE:

Are you passionate about driving innovation in the data storage industry? Are you skilled in crafting technical solutions that exceed customer expectations? If so, we have an exciting opportunity for you! Everpure (formerly Pure Storage), a leader in the data storage and flash technology space, is seeking a talented and motivated Senior Pre-Sales Systems Engineer to join our dynamic team. 

As a Senior Pre-Sales Systems Engineer, you will play a crucial role in understanding our customers' unique challenges and tailoring Everpure solutions to meet their specific needs. Collaborating closely with the sales team, you will act as a technical expert during the sales process, helping to showcase the value of our products and services.

WHAT YOU’LL DO:

• Develop an exhaustive understanding of what drives a customer’s business and what motivates their decision making
• Connect the dots from technology solutions, inclusive of the Everpure portfolio and others from the ecosystem, to measurable customer business outcomes
• Partner closely with account managers, specialists and channel partners to create a seamless and holistic customer experience and strategy to drive revenue growth and net new business
• Delight customers and teammates with your technical leadership and domain expertise on storage products, distributed storage architectures, file systems, and competitive storage offerings in the DAS, NAS and SAN product spaces
• Take control of evaluations,  benchmarks and system configurations
• Build and deliver technical product and architecture presentations with vigor to customers and lock in the technical win with clients and prospective accounts
• Capture requirements and translate Customer’s business needs into innovative solutions to accelerate their growth and capacity
• Seek out and spur new opportunities for interoperability, functional, and performance testing/validation
• Promote mutual roadmap and planning exchanges
• Liaise with product and technical marketing to produce materials (i.e. whitepaper, web presentations) that support overall alliance plans and objectives
• Stay current with the competition and ensure that materials accurately reflect the latest, differentiated solution positioning
• Move with market trends and competitive landscape to promote thought leadership within our organization
• Lead by example living the Everpure Values:  Persistence, Creativity, Teamwork, Ownership and Customer-first  

WHAT YOU BRING:

• Pre-sales experience is required
• 5 or more years of relevant experience, mixed among technology, design, and communications required. Experience supporting the sales of enterprise storage, networking, systems, cloud, or software to enterprise accounts preferred
• Deep understanding of the architecture, design and implementation of multi-tiered client/server and web-based computing solutions
• Must have a familiarity with modern web architecture a plus (LAMP stack, scale-out vs scale-up architectures, AWS well-architected framework, microservices architecture)
• Prior experience in targeting new prospects and converting them into clients
• Contribute significant portions and/or lead responses to RFPs, RFQs and RFIs
• Superior knowledge of current and emerging storage architectures (FC, iSCSI, NAS, OSD, SAN)
• Previous experience with Linux, NFS file systems and Linux distributed network environment
• Installation/configuration of distributed computing, multiprocessing, virtual memory subsystem, storage subsystems architecture, shared memory architectures, cache architectures, windowing systems
• Strong knowledge of digital transformation to a Cloud Native architecture, On-Prem, Public Cloud, Provisioning Automation, and Containers
• Knowledge of VMware, Local Area Networking, Ethernet, TCP/IP and general networking
• Familiarity with AWS, Azure, GCP, containers, k8s and microservices architectures a plus
• Curiosity and passion around technology and explaining and showing new technology platforms and concepts to customers
• Familiarity with storage-intensive applications and their requirements such as structured databases (SQL, Oracle) is highly desirable
• Excellent verbal and written interpersonal skills

#LI-REMOTE

#LI-JL4

Overview of Role

66degrees’ Managed Cloud Optimization (MCO) team works with some of the largest cloud users in the world to help them transform their businesses with technology. Our Site Reliability Engineers (SREs) combine Google Cloud Platform expertise with a passion for devops methodologies to help our clients maintain, optimize, and scale their cloud implementations.

On a daily basis, our SREs work with varied and exciting customers on topics ranging from solving critical outages to designing and deploying new cloud workloads to building self-healing automation. Our SREs work with cutting-edge Google Cloud technologies like Google Kubernetes Engine (GKE), Anthos, BigQuery and data pipelines, as well as leading 3rd party tools like Prometheus, Datadog, and many others. Our SREs also work with languages like Python and Terraform to create automation, deploy infrastructure, and contribute to open-sourcing.

If you’re looking to continually build and apply your Google Cloud expertise to new and varied environments while acting as a key contributor to building the best Google consulting partner in the industry – let’s talk.

Note: Pacific and Mountain Time Zones preferred; This role has a weekend on-call rotation

Responsibilities

• Ensuring near-zero downtime with monitoring and alerting, self-healing automation, and continuous improvement
• Create highly automated, available and scalable systems by applying software and infrastructure principles
• Employ and advise clients on DevOps and SRE principles and practices, covering deployment pipelines, HA, service reliability, technical debt, and operational toil for live services running at scale
• Provide a proactive approach to our clients’ workloads, anticipating failures, automating tasks, ensuring availability, and providing a great customer experience
• Work closely with clients, your team, and Google engineers to investigate and resolve infrastructure issues
• Manage a Jira queue of inbound requests for numerous clients while effectively balancing and prioritizing projects
• Contribute to ad-hoc initiatives such as writing documentation, open-sourcing, and improving operation, making a huge impact at a rapid-growth Google Premier Partner

Qualifications

• Minimum 4+ years of cloud and infrastructure experience, including demonstrated expertise with Linux, Windows, k8s, databases, and networking services
• 2+ years of full-time Google Cloud experience preferred
• Proficiency with Python required. Other programming language experience is a plus
• Strong provisioning and configuration skills using Terraform
• Experience in troubleshooting that spans systems, network, and code
• Microsoft Server and SQL Server experience is a plus but not required
• Experience with 24x7x365 monitoring, incident response, and on-call support preferred
• Experience determining & negotiating Error budgets, SLIs, SLOs, and SLAs with product owners
• Demonstrate the ability to work independently and as a member of a greater team, including cross-team activities
• Experience working in Agile Scrum, Kanban methodologies in SDLC
• Proven experience balancing service reliability, metrics, sustainability, technical debt, and operational toil for live services running at scale
• Strong communication skills, as this is a heavily customer-facing role
• A Bachelor’s degree in Computer Science, Computer Engineering, or related or equivalent work experience required.

Engineering at Brex

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

As a Senior Application Security Engineer, you will focus on finding and responding to security vulnerabilities across the Brex platform. In this role, you will perform code reviews, design reviews, penetration testing, and vulnerability management. You will develop and maintain tooling to perform static and dynamic testing of the Brex platform and tooling which supports secure developer workflows. Application Security is part of our wider Financial Scale organization, which means you will work closely with Security Operations, GRC, Product Security, Front End Platform,  IT Infrastructure teams.

We’re looking for individuals with a strong background and interest in penetration testing. You should have a demonstrated ability to find vulnerabilities in complex systems and craft exploits to demonstrate business impact. This role is highly cross functional and collaborative, you will have the opportunity to work with every engineering team across Brex. You should be enthusiastic about working with a variety of backgrounds, roles, and needs. Building a world-class financial service requires world-class security. 

Brex is pioneering the next wave of AI-driven financial services for dynamic, high-impact companies like Coinbase, Robinhood, and Anthropic. We're at the early stages of integrating AI across our product suite, this role will have the opportunity to influence and secure the future of AI Security at Brex. You'll be at the forefront of securing our novel AI implementations, identifying attack vectors in agentic-powered features, and partnering with product and engineering teams to build AI capabilities that our customers can trust with their critical financial operations.

Responsibilities

• Identifying vulnerabilities, demonstrating business impact, and articulating the risk of specific vulnerabilities to drive prioritization efforts
• Perform penetration testing and design reviews, looking for vulnerabilities and insecure designs, work with engineering and product to design secure product features
• Maintain and build internal tools to automate security efforts, perform SAST and DAST testing of the Brex platform, and support secure development practices
• Build and contribute to a culture of collaborative security excellence through technical leadership, learning sessions, and mentorship within the team and wider organization

Requirements

• 5+ years work experience in an Application Security or related role
• Ability to find vulnerabilities in complex systems, demonstrating business impact through custom attack chains
• Experience with a wide range of secure development activities including— threat modeling, developer education, and incident response
• Knowledge of Python, scripting languages, and AI/agentic workflows to automate tasks, build tools and improve productivity
• Collaborative mindset paired with strong written and verbal communication skills

Bonus points

• Proficiency with Kotlin, gRPC, GraphQL, Kubernetes
• Previous experience as a software engineer
• Consultancy experience performing web application security reviews
• Experience with securing distributed systems in AWS and cloud environments
• Experience with pentesting and securing agentic features and systems
• Contributions to the wider technical community— open source, public research, mentorship, community organizing, blogging, CVEs, presentations, etc
• Experience submitting to bug bounty programs or responsible disclosure programs

Compensation

The expected salary range for this role is $192,000 - $240,000. 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.

Engineering at Brex

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

As an Application Security Engineer, you will contribute to finding and responding to security vulnerabilities across the Brex platform. In this role, you will participate in code reviews, design reviews, penetration testing, and vulnerability management. You will contribute to tooling that performs static and dynamic testing of the Brex platform and supports secure developer workflows. Application Security is part of our wider Financial Scale organization, which means you will work closely with Security Operations, GRC, Product Security, Front End Platform, and IT Infrastructure teams.

We're looking for individuals with a solid foundation in penetration testing and a curiosity for finding vulnerabilities in complex systems. You should have experience identifying and documenting vulnerabilities across common vulnerability classes and be able to communicate their risk clearly to engineering and product teams. This role is highly cross-functional — you'll have the opportunity to collaborate with engineering teams across Brex and grow your security expertise in a fast-moving environment.

Brex is pioneering the next wave of AI-driven financial services for dynamic, high-impact companies like Coinbase, Robinhood, and Anthropic. As we integrate AI across our product suite, this role will give you hands-on experience contributing to AI security at Brex. You'll apply emerging AI security best practices to help secure our agentic features, identify attack surfaces introduced by LLM-powered systems, and partner with product and engineering teams to build AI capabilities our customers can trust with their critical financial operations.

Responsibilities

• Identify vulnerabilities across common vulnerability classes (e.g., OWASP Top 10), document findings clearly, and communicate risk to drive remediation efforts
• Participate in penetration testing and design reviews alongside senior engineers, contributing to the identification of vulnerabilities and insecure designs
• Contribute to internal tooling and automation efforts that support SAST and DAST testing of the Brex platform and promote secure development practices
• Collaborate with engineering and product teams to support the design of secure product features
• Actively contribute to a culture of security awareness through knowledge sharing and peer learning

Requirements

• 4+ years of work experience in Application Security or a related role
• Demonstrated ability to find and document vulnerabilities in complex systems, with clear communication of business risk
• Hands-on experience with a subset of secure development activities, such as code review, threat modeling, or penetration testing
• Experience identifying security risks in AI/ML systems — such as prompt injection, model manipulation, or data poisoning — through work experience, personal projects, CTFs, or bug bounties
• Familiarity with agentic workflows and the ability to reason about attack surfaces introduced by LLM-powered features
• Knowledge of Python or scripting languages to automate tasks and build tooling
• Collaborative mindset paired with strong written and verbal communication skills

Bonus points

• Experience with Kotlin, gRPC, GraphQL, Kubernetes
• Previous experience as a software engineer
• Experience with securing distributed systems in AWS and cloud environments
• Experience with web application security reviews
• Contributions to the wider technical community — open source, public research, CTF participation, blogging, CVEs, or presentations
• Experience submitting to bug bounty or responsible disclosure programs
• Published AI security research or contributions to AI security frameworks

Compensation

The expected salary range for this role is $152,000 - $190,000. 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 a Sr. Software Engineer in Tel Cloud, you will own the components that power our global communications systems. You will work on features like call routing, SMS/MMS messaging, spam detection, fraud detection, fleet deployments, porting, and number management, ensuring our platform remains scalable, reliable, and trustworthy.

This position reports to an Engineering Manager in the Telephony Platform team.

We don’t mind if you come from a different engineering background or haven’t worked in communications before. Just be excited to learn, contribute to the team, and build a fast, reliable, elegant product that delights our customers.

What you’ll do

• Design data models for heavy concurrency and real-time performance, ensuring sub-second latency for global call routing.
• Test and tune service scaling to ensure we always have capacity available to service our customers’ real-time communications.
• Build monitors and alerts to maintain high reliability and observability.
• Participate in releases and on-call rotations, driving operational excellence for the team's platform components.
• Design, write, and deploy features used by Dialpad engineering teams to communicate with carriers and third-party communication services.
• Strategize and drive the roadmap for cross-team platform initiatives.
• Serve as a champion, coach, and mentor to more junior engineers, promoting a culture of ownership and craftsmanship.

Skills you’ll bring  

• Bachelor's degree in Computer Science or equivalent practical experience.
• 5+ years of SaaS professional experience maintaining large-scale production backend systems.
• Demonstrated proficiency in coding with AI agents to accelerate development and improve code quality.
• Deep expertise in Python/Java/C and at least one cloud-native architecture (e.g., GCP).
• Familiarity with async and MapReduce design patterns, as well as NoSQL databases, distributed caches, and large-scale data lakes.
• Experience in profiling and optimizing backend code for low-latency requirements (p50/p90 metrics).
• A strong sense of urgency, personal agency, and customer empathy.
• Passion for data-driven decisions, building resilient systems, and solving classes of problems.

Our tech stack

• Backend: Python, Google Cloud Platform, Cloud Run / k8s, Datastore, Redis, ElasticSearch, BigQuery, Google Cloud Pub/Sub.
• Frontend: Angular / Bootstrap.

Your role
As a Sr. SDET in Agentic QA, you will own the test automation and quality frameworks that support Dialpad’s AI Voice Agent services. You will develop automated tests for end-to-end product experiences, from frontend UI to backend services to APIs to audio/text interactions. You will test orchestration flows, agent configuration experiences, and guardian safeguards to create robust automated coverage for functionality, performance, reliability, UX, and more. 

In this role, you will develop substantial amounts of automated test infrastructure and partner deeply with the development team to make our fast-growing AI platform more testable, more stable, and more delightful for customers.

This position is based at one of Dialpad’s Canadian offices and reports to a QA Eng Manager in the United States.

What you’ll do

• Own end-to-end quality for agentic features and workflows, including strategy, development, execution, and release qualification.
• Design and build automation tooling and frameworks for AI/LLM-driven systems, including prompt flows, agent orchestration, and tool integrations.
• Develop and maintain evaluation frameworks (evals) to measure response quality, accuracy, and hallucination rates.
• Drive automation coverage (80%+ for critical AI workflows) using deterministic + probabilistic validation approaches.
• Integrate AI quality checks into CI/CD pipelines with fast feedback cycles (<15 minutes for PR validation).
• Build tooling for LLM observability and debugging, including prompt tracing and response analysis.
• Partner with Applied AI teams on prompt engineering, model selection, and evaluation strategies.
• Design and execute performance and load tests for AI services (latency, throughput, cost efficiency).
• Identify and mitigate risks related to hallucinations, bias, safety, and edge cases.
• Define and track AI quality KPIs (task success rates, precision/recall, latency, etc.).
• Participate in design and architecture reviews to ensure systems are testable, observable, and resilient.
• Mentor engineers and contribute to raising the bar on AI quality engineering practices.

What you’ll bring

• 5+ years of experience in software engineering or SDET roles with an emphasis on software development.
• Strong programming skills in Python (preferred), Java, or JavaScript.
• Experience testing distributed, cloud-native SaaS systems and APIs.
• Demonstrated proficiency in coding with AI agents to accelerate development and improve code quality.
• Hands-on exposure to LLMs or AI/ML systems (e.g., OpenAI, Claude, Gemini, or similar platforms).
• Understanding of non-deterministic systems and probabilistic testing approaches.
• Experience building test frameworks and scalable automation systems.
• Familiarity with AI evaluation techniques (benchmarking, golden datasets, human-in-the-loop validation).
• Experience with CI/CD pipelines (e.g., Jenkins, GitHub Actions).
• Strong collaboration skills with the ability to work across distributed teams and time zones.
• Bachelor’s degree in Computer Science or equivalent practical experience.
• Backend: Python, Go, Google Cloud Platform, Cloud Run / App Engine, Kubernetes, Datastore, Redis, ElasticSearch.
• Frontend: Vue3, React.
• AI Stack: LLM APIs, LiveKit, prompt orchestration frameworks, evaluation tooling.

Your role
As a Sr. SDET in Agentic QA, you will own the test automation and quality frameworks that support Dialpad’s AI Voice Agent services. You will develop automated tests for end-to-end product experiences, from frontend UI to backend services to APIs to audio/text interactions. You will test orchestration flows, agent configuration experiences, and guardian safeguards to create robust automated coverage for functionality, performance, reliability, UX, and more. 

In this role, you will develop substantial amounts of automated test infrastructure and partner deeply with the development team to make our fast-growing AI platform more testable, more stable, and more delightful for customers.

This position is based at one of Dialpad’s Canadian offices and reports to a QA Eng Manager in the United States.

What you’ll do

• Own end-to-end quality for agentic features and workflows, including strategy, development, execution, and release qualification.
• Design and build automation tooling and frameworks for AI/LLM-driven systems, including prompt flows, agent orchestration, and tool integrations.
• Develop and maintain evaluation frameworks (evals) to measure response quality, accuracy, and hallucination rates.
• Drive automation coverage (80%+ for critical AI workflows) using deterministic + probabilistic validation approaches.
• Integrate AI quality checks into CI/CD pipelines with fast feedback cycles (<15 minutes for PR validation).
• Build tooling for LLM observability and debugging, including prompt tracing and response analysis.
• Partner with Applied AI teams on prompt engineering, model selection, and evaluation strategies.
• Design and execute performance and load tests for AI services (latency, throughput, cost efficiency).
• Identify and mitigate risks related to hallucinations, bias, safety, and edge cases.
• Define and track AI quality KPIs (task success rates, precision/recall, latency, etc.).
• Participate in design and architecture reviews to ensure systems are testable, observable, and resilient.
• Mentor engineers and contribute to raising the bar on AI quality engineering practices.

What you’ll bring

• 5+ years of experience in software engineering or SDET roles with an emphasis on software development.
• Strong programming skills in Python (preferred), Java, or JavaScript.
• Experience testing distributed, cloud-native SaaS systems and APIs.
• Demonstrated proficiency in coding with AI agents to accelerate development and improve code quality.
• Hands-on exposure to LLMs or AI/ML systems (e.g., OpenAI, Claude, Gemini, or similar platforms).
• Understanding of non-deterministic systems and probabilistic testing approaches.
• Experience building test frameworks and scalable automation systems.
• Familiarity with AI evaluation techniques (benchmarking, golden datasets, human-in-the-loop validation).
• Experience with CI/CD pipelines (e.g., Jenkins, GitHub Actions).
• Strong collaboration skills with the ability to work across distributed teams and time zones.
• Bachelor’s degree in Computer Science or equivalent practical experience.
• Backend: Python, Go, Google Cloud Platform, Cloud Run / App Engine, Kubernetes, Datastore, Redis, ElasticSearch.
• Frontend: Vue3, React.
• AI Stack: LLM APIs, LiveKit, prompt orchestration frameworks, evaluation tooling.

About this position:

We’re looking for a Machine Learning Infrastructure Engineer to join our growing Data & Platform team and build the foundation that powers our AI and machine learning capabilities across Later’s product portfolio. As our first dedicated ML Infrastructure Engineer, you will own the systems that support model experimentation, training, deployment, and monitoring at scale.

This role is critical to accelerating our data science initiatives and enabling future AI innovation. You’ll design and operate reliable, secure, and scalable ML infrastructure that empowers data scientists and engineers to ship high-impact models with confidence. If you’re excited about building robust ML systems in a fast-moving environment—and want to define the standard for ML Ops at Later—this is your opportunity.

What you'll be doing:

Strategy

• Define and own the long-term ML infrastructure roadmap, ensuring it supports both current experimentation needs and future AI initiatives.
• Establish best practices for model lifecycle management, deployment standards, monitoring, and governance. 
• Identify infrastructure gaps and proactively design scalable solutions to enable high-velocity ML development.
• Contribute to cross-functional technical planning, ensuring ML systems align with product and platform strategy.

Technical/ Execution

• Design, build, and maintain production-grade model deployment and inference systems using CI/CD pipelines, containerized services (Docker), and API frameworks (e.g., Flask).
• Automate end-to-end ML lifecycle workflows including training pipelines, model validation, registry management, deployment, and rollback strategies.
• Implement robust monitoring systems for model performance, latency, drift detection, and infrastructure health using tools such as CloudWatch, Prometheus, and Grafana.
• Operate across AWS and GCP environments to manage training and inference workloads, including GPU-based infrastructure and BigQuery datasets.
• Develop and maintain infrastructure-as-code (Terraform, CloudFormation) to ensure scalable, repeatable, and secure cloud environments.
• Implement and optimize CI/CD workflows (e.g., GitHub Actions, GitLab CI, Bitbucket Pipelines) for ML and infrastructure automation.

Team / Collaboration

• Partner closely with Data Scientists, Analysts, Platform Engineers, and Product Engineers to support end-to-end ML workflows.
• Translate data science experimentation needs into production-ready infrastructure solutions.
• Serve as the technical bridge between ML experimentation and productized deployment.
• Share knowledge and best practices to elevate ML maturity across teams.

Research/Best Practices

• Stay current on emerging ML Ops practices, tools, and frameworks to continuously improve system reliability and efficiency.
• Evaluate and implement model-serving frameworks (e.g., TorchServe, Seldon, TensorRT) where appropriate.
• Contribute to governance, reproducibility, and auditability standards for ML systems.
• Experiment with new tooling and workflows to improve reproducibility, performance, and developer velocity.

What success looks like:

• ML models move from experimentation to production quickly and reliably, with minimal manual intervention.
• CI/CD pipelines enable safe, repeatable deployments with clear rollback strategies.
• Model performance, drift, and infrastructure health are proactively monitored and observable.
• Infrastructure supports scalable GPU training and real-time inference without bottlenecks.
• Data scientists report improved velocity, reproducibility, and confidence in deploying models.
• ML systems are secure, compliant, and aligned with evolving product and AI strategy.

What you bring:

• 4+ years of experience in ML Ops, ML infrastructure, backend engineering, or related roles supporting production ML systems.
• Experience working in cloud-native environments (AWS and/or GCP) with hands-on deployment of ML workloads.
• Proven track record designing and implementing CI/CD pipelines for ML systems.
• Strong experience with Amazon SageMaker, Docker, Flask-based APIs, and infrastructure automation tools.
• Hands-on experience with ML lifecycle tooling such as MLflow, SageMaker Studio, or Weights & Biases.
• Experience managing container orchestration platforms (Kubernetes, EKS, or GKE).
• Strong programming experience in Python (additional experience in Go, Java, or Scala is a plus).
• Experience working with infrastructure-as-code tools such as Terraform or CloudFormation.
• Familiarity with observability tools such as CloudWatch, Prometheus, Grafana, Datadog, or centralized logging platforms.
• Experience managing GPU-based workloads and scaling training/inference systems.
• Familiarity with data infrastructure tools such as BigQuery and cloud-native data pipelines.
• Bonus: Experience supporting LLMs or generative AI pipelines, distributed training systems, feature stores (e.g., Feast), real-time inference systems, or ML governance frameworks.
• A mindset focused on automation, reliability, performance, and continuous improvement in fast-scaling environments.

How you work: 

• Driven by Impact: You deliver results that matter—prioritizing high-value work, meeting deadlines, and adapting quickly while keeping outcomes clear.
• Strategic & Customer-Centric: You anticipate risks and opportunities, connect decisions to long-term growth, and build trust through proactive insights.
• Curious & Growth-Oriented: You seek knowledge, ask sharp questions, and apply learnings fast—challenging the status quo with a mindset of improvement.
• Collaborative & Resilient: You thrive in change by staying resourceful, solution-focused, and positive—removing roadblocks, sharing insights, and keeping morale high.
• Accountable & Honest: You own your work, hold yourself and others to a high bar, and use transparent feedback to drive growth.
• Emotionally Intelligent: You build trust through empathy and collaboration, foster inclusion, and inspire others with grit, optimism, and integrity.

Our approach to compensation:

We take a market-based & data-driven approach to compensation. We leverage data from trusted third-party compensation sources to help us understand the market value of a role based on function, level, geographic location, and scope. We evaluate compensation bi-annually, including performance and market-related factors.

Our salaries are benchmarked against market Total Cash Compensation for the geographic location of our job posting. Compensation for some roles is structured as On Target Earnings (OTE = base + commission/variable) while for others it is structured as Salary only.

To comply with local legislation and ensure transparency, we share salary ranges on all job postings. Skills, experience and other factors help determine the final salary we offer which may vary from the original range posted. 

Additionally, all permanent team members are eligible to participate in various benefits plans as part of their overall compensation package.

Salary Range: 

$ 145,000 -165,000 

#LI-remote

About this position:

We’re looking for a Machine Learning Infrastructure Engineer to join our growing Data & Platform team and build the foundation that powers our AI and machine learning capabilities across Later’s product portfolio. As our first dedicated ML Infrastructure Engineer, you will own the systems that support model experimentation, training, deployment, and monitoring at scale.

This role is critical to accelerating our data science initiatives and enabling future AI innovation. You’ll design and operate reliable, secure, and scalable ML infrastructure that empowers data scientists and engineers to ship high-impact models with confidence. If you’re excited about building robust ML systems in a fast-moving environment—and want to define the standard for ML Ops at Later—this is your opportunity.

What you'll be doing:

Strategy

• Define and own the long-term ML infrastructure roadmap, ensuring it supports both current experimentation needs and future AI initiatives.
• Establish best practices for model lifecycle management, deployment standards, monitoring, and governance. 
• Identify infrastructure gaps and proactively design scalable solutions to enable high-velocity ML development.
• Contribute to cross-functional technical planning, ensuring ML systems align with product and platform strategy.

Technical/ Execution

• Design, build, and maintain production-grade model deployment and inference systems using CI/CD pipelines, containerized services (Docker), and API frameworks (e.g., Flask).
• Automate end-to-end ML lifecycle workflows including training pipelines, model validation, registry management, deployment, and rollback strategies.
• Implement robust monitoring systems for model performance, latency, drift detection, and infrastructure health using tools such as CloudWatch, Prometheus, and Grafana.
• Operate across AWS and GCP environments to manage training and inference workloads, including GPU-based infrastructure and BigQuery datasets.
• Develop and maintain infrastructure-as-code (Terraform, CloudFormation) to ensure scalable, repeatable, and secure cloud environments.
• Implement and optimize CI/CD workflows (e.g., GitHub Actions, GitLab CI, Bitbucket Pipelines) for ML and infrastructure automation.

Team / Collaboration

• Partner closely with Data Scientists, Analysts, Platform Engineers, and Product Engineers to support end-to-end ML workflows.
• Translate data science experimentation needs into production-ready infrastructure solutions.
• Serve as the technical bridge between ML experimentation and productized deployment.
• Share knowledge and best practices to elevate ML maturity across teams.

Research/Best Practices

• Stay current on emerging ML Ops practices, tools, and frameworks to continuously improve system reliability and efficiency.
• Evaluate and implement model-serving frameworks (e.g., TorchServe, Seldon, TensorRT) where appropriate.
• Contribute to governance, reproducibility, and auditability standards for ML systems.
• Experiment with new tooling and workflows to improve reproducibility, performance, and developer velocity.

What success looks like:

• ML models move from experimentation to production quickly and reliably, with minimal manual intervention.
• CI/CD pipelines enable safe, repeatable deployments with clear rollback strategies.
• Model performance, drift, and infrastructure health are proactively monitored and observable.
• Infrastructure supports scalable GPU training and real-time inference without bottlenecks.
• Data scientists report improved velocity, reproducibility, and confidence in deploying models.
• ML systems are secure, compliant, and aligned with evolving product and AI strategy.

What you bring:

• 4+ years of experience in ML Ops, ML infrastructure, backend engineering, or related roles supporting production ML systems.
• Experience working in cloud-native environments (AWS and/or GCP) with hands-on deployment of ML workloads.
• Proven track record designing and implementing CI/CD pipelines for ML systems.
• Strong experience with Amazon SageMaker, Docker, Flask-based APIs, and infrastructure automation tools.
• Hands-on experience with ML lifecycle tooling such as MLflow, SageMaker Studio, or Weights & Biases.
• Experience managing container orchestration platforms (Kubernetes, EKS, or GKE).
• Strong programming experience in Python (additional experience in Go, Java, or Scala is a plus).
• Experience working with infrastructure-as-code tools such as Terraform or CloudFormation.
• Familiarity with observability tools such as CloudWatch, Prometheus, Grafana, Datadog, or centralized logging platforms.
• Experience managing GPU-based workloads and scaling training/inference systems.
• Familiarity with data infrastructure tools such as BigQuery and cloud-native data pipelines.
• Bonus: Experience supporting LLMs or generative AI pipelines, distributed training systems, feature stores (e.g., Feast), real-time inference systems, or ML governance frameworks.
• A mindset focused on automation, reliability, performance, and continuous improvement in fast-scaling environments.

How you work: 

• Driven by Impact: You deliver results that matter—prioritizing high-value work, meeting deadlines, and adapting quickly while keeping outcomes clear.
• Strategic & Customer-Centric: You anticipate risks and opportunities, connect decisions to long-term growth, and build trust through proactive insights.
• Curious & Growth-Oriented: You seek knowledge, ask sharp questions, and apply learnings fast—challenging the status quo with a mindset of improvement.
• Collaborative & Resilient: You thrive in change by staying resourceful, solution-focused, and positive—removing roadblocks, sharing insights, and keeping morale high.
• Accountable & Honest: You own your work, hold yourself and others to a high bar, and use transparent feedback to drive growth.
• Emotionally Intelligent: You build trust through empathy and collaboration, foster inclusion, and inspire others with grit, optimism, and integrity.

Our approach to compensation:

We take a market-based & data-driven approach to compensation. We leverage data from trusted third-party compensation sources to help us understand the market value of a role based on function, level, geographic location, and scope. We evaluate compensation bi-annually, including performance and market-related factors.

Our salaries are benchmarked against market Total Cash Compensation for the geographic location of our job posting. Compensation for some roles is structured as On Target Earnings (OTE = base + commission/variable) while for others it is structured as Salary only.

To comply with local legislation and ensure transparency, we share salary ranges on all job postings. Skills, experience and other factors help determine the final salary we offer which may vary from the original range posted. 

Additionally, all permanent team members are eligible to participate in various benefits plans as part of their overall compensation package.

Salary Range: 

$ 145,000 -165,000 

#LI-remote

About this position:

We’re looking for a Machine Learning Infrastructure Engineer to join our growing Data & Platform team and build the foundation that powers our AI and machine learning capabilities across Later’s product portfolio. As our first dedicated ML Infrastructure Engineer, you will own the systems that support model experimentation, training, deployment, and monitoring at scale.

This role is critical to accelerating our data science initiatives and enabling future AI innovation. You’ll design and operate reliable, secure, and scalable ML infrastructure that empowers data scientists and engineers to ship high-impact models with confidence. If you’re excited about building robust ML systems in a fast-moving environment—and want to define the standard for ML Ops at Later—this is your opportunity.

What you'll be doing:

Strategy

• Define and own the long-term ML infrastructure roadmap, ensuring it supports both current experimentation needs and future AI initiatives.
• Establish best practices for model lifecycle management, deployment standards, monitoring, and governance. 
• Identify infrastructure gaps and proactively design scalable solutions to enable high-velocity ML development.
• Contribute to cross-functional technical planning, ensuring ML systems align with product and platform strategy.

Technical/ Execution

• Design, build, and maintain production-grade model deployment and inference systems using CI/CD pipelines, containerized services (Docker), and API frameworks (e.g., Flask).
• Automate end-to-end ML lifecycle workflows including training pipelines, model validation, registry management, deployment, and rollback strategies.
• Implement robust monitoring systems for model performance, latency, drift detection, and infrastructure health using tools such as CloudWatch, Prometheus, and Grafana.
• Operate across AWS and GCP environments to manage training and inference workloads, including GPU-based infrastructure and BigQuery datasets.
• Develop and maintain infrastructure-as-code (Terraform, CloudFormation) to ensure scalable, repeatable, and secure cloud environments.
• Implement and optimize CI/CD workflows (e.g., GitHub Actions, GitLab CI, Bitbucket Pipelines) for ML and infrastructure automation.

Team / Collaboration

• Partner closely with Data Scientists, Analysts, Platform Engineers, and Product Engineers to support end-to-end ML workflows.
• Translate data science experimentation needs into production-ready infrastructure solutions.
• Serve as the technical bridge between ML experimentation and productized deployment.
• Share knowledge and best practices to elevate ML maturity across teams.

Research/Best Practices

• Stay current on emerging ML Ops practices, tools, and frameworks to continuously improve system reliability and efficiency.
• Evaluate and implement model-serving frameworks (e.g., TorchServe, Seldon, TensorRT) where appropriate.
• Contribute to governance, reproducibility, and auditability standards for ML systems.
• Experiment with new tooling and workflows to improve reproducibility, performance, and developer velocity.

What success looks like:

• ML models move from experimentation to production quickly and reliably, with minimal manual intervention.
• CI/CD pipelines enable safe, repeatable deployments with clear rollback strategies.
• Model performance, drift, and infrastructure health are proactively monitored and observable.
• Infrastructure supports scalable GPU training and real-time inference without bottlenecks.
• Data scientists report improved velocity, reproducibility, and confidence in deploying models.
• ML systems are secure, compliant, and aligned with evolving product and AI strategy.

What you bring:

• 4+ years of experience in ML Ops, ML infrastructure, backend engineering, or related roles supporting production ML systems.
• Experience working in cloud-native environments (AWS and/or GCP) with hands-on deployment of ML workloads.
• Proven track record designing and implementing CI/CD pipelines for ML systems.
• Strong experience with Amazon SageMaker, Docker, Flask-based APIs, and infrastructure automation tools.
• Hands-on experience with ML lifecycle tooling such as MLflow, SageMaker Studio, or Weights & Biases.
• Experience managing container orchestration platforms (Kubernetes, EKS, or GKE).
• Strong programming experience in Python (additional experience in Go, Java, or Scala is a plus).
• Experience working with infrastructure-as-code tools such as Terraform or CloudFormation.
• Familiarity with observability tools such as CloudWatch, Prometheus, Grafana, Datadog, or centralized logging platforms.
• Experience managing GPU-based workloads and scaling training/inference systems.
• Familiarity with data infrastructure tools such as BigQuery and cloud-native data pipelines.
• Bonus: Experience supporting LLMs or generative AI pipelines, distributed training systems, feature stores (e.g., Feast), real-time inference systems, or ML governance frameworks.
• A mindset focused on automation, reliability, performance, and continuous improvement in fast-scaling environments.

How you work: 

• Driven by Impact: You deliver results that matter—prioritizing high-value work, meeting deadlines, and adapting quickly while keeping outcomes clear.
• Strategic & Customer-Centric: You anticipate risks and opportunities, connect decisions to long-term growth, and build trust through proactive insights.
• Curious & Growth-Oriented: You seek knowledge, ask sharp questions, and apply learnings fast—challenging the status quo with a mindset of improvement.
• Collaborative & Resilient: You thrive in change by staying resourceful, solution-focused, and positive—removing roadblocks, sharing insights, and keeping morale high.
• Accountable & Honest: You own your work, hold yourself and others to a high bar, and use transparent feedback to drive growth.
• Emotionally Intelligent: You build trust through empathy and collaboration, foster inclusion, and inspire others with grit, optimism, and integrity.

Our approach to compensation:

We take a market-based & data-driven approach to compensation. We leverage data from trusted third-party compensation sources to help us understand the market value of a role based on function, level, geographic location, and scope. We evaluate compensation bi-annually, including performance and market-related factors.

Our salaries are benchmarked against market Total Cash Compensation for the geographic location of our job posting. Compensation for some roles is structured as On Target Earnings (OTE = base + commission/variable) while for others it is structured as Salary only.

To comply with local legislation and ensure transparency, we share salary ranges on all job postings. Skills, experience and other factors help determine the final salary we offer which may vary from the original range posted. 

Additionally, all permanent team members are eligible to participate in various benefits plans as part of their overall compensation package.

Salary Range: 

$ 145,000 -165,000 

#LI-remote

The mission of Speechify is to make sure that reading is never a barrier to learning.

Over 50 million people use Speechify’s text-to-speech products to turn whatever they’re reading – PDFs, books, Google Docs, news articles, websites – into audio, so they can read faster, read more, and remember more. Speechify’s text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its 2025 Design Award winner for Inclusivity.  

Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting – Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies.

Overview

The responsibilities of our Platform team include building and maintaining all backend services, including, but not limited to, payments, analytics, subscriptions, new products, text to speech, and external APIs.

This is a key role and ideal for someone who thinks strategically, enjoys fast-paced environments, is passionate about making product decisions, and has experience building great user experiences that delight users.

We are a flat organization that allows anyone to become a leader by showing excellent technical skills and delivering results consistently and fast. Work ethic, solid communication skills, and obsession with winning are paramount. 

Our interview process involves several technical interviews and we aim to complete them within 1 week. 

What You’ll Do

• Design, develop, and maintain robust APIs including public TTS API, internal APIs like Payment, Subscription, Auth and Consumption Tracking, ensuring they meet business and scalability requirements
• Oversee the full backend API landscape, enhancing and optimizing for performance and maintainability
• Collaborate on B2B solutions, focusing on customization and integration needs for enterprise clients
• Work closely with cross-functional teams to align backend architecture with overall product strategy and user experience

An Ideal Candidate Should Have

• Proven experience in backend development: TS/Node (required)
• Direct experience with GCP and knowledge of AWS, Azure, or other cloud providers
• Efficiency in ideation and implementation, prioritizing tasks based on urgency and impact
• Preferred: Experience with Docker and containerized deployments
• Preferred: Proficiency in deploying high availability applications on Kubernetes

What We Offer

• A dynamic environment where your contributions shape the company and its products
• A team that values innovation, intuition, and drive
• Autonomy, fostering focus and creativity
• The opportunity to have a significant impact in a revolutionary industry
• Competitive compensation, a welcoming atmosphere, and a commitment to an exceptional asynchronous work culture
• The privilege of working on a product that changes lives, particularly for those with learning differences like dyslexia, ADD, and more
• An active role at the intersection of artificial intelligence and audio – a rapidly evolving tech domain

Think you’re a good fit for this job? 

Tell us more about yourself and why you're interested in the role when you apply.
And don’t forget to include links to your portfolio and LinkedIn.

Not looking but know someone who would make a great fit? 

Refer them! 

Speechify is committed to a diverse and inclusive workplace. 

Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

The Opportunity

We're looking for a Senior Software Engineer to join our Web Data team and help build the next generation of ZoomInfo's web crawling and data extraction infrastructure.

This is a hands-on engineering role with high impact. You'll work alongside experienced engineers building large-scale crawling and extraction systems that process billions of pages. Your day-to-day will involve solving real distributed systems problems, writing production code, and shipping features that directly impact data quality across the platform.

You'll partner with a dedicated people manager who handles HR and administrative responsibilities, a product manager who connects business needs with technical work, and a senior manager who removes roadblocks and supports career growth. Your focus is on engineering execution, technical excellence, and collaboration.

What You'll Do

As a Senior Software Engineer, you'll contribute to enterprise-scale crawling and extraction platforms that process massive volumes of web data.

You will:

• Design and implement components of scalable, fault-tolerant web crawling and extraction pipelines
• Write clean, production-grade code in Java and Python
• Build and operate ETL/ELT pipelines for large-scale data extraction and transformation
• Work with cloud infrastructure on GCP and AWS, primarily on GKE
• Improve observability, reliability, and operational excellence across the systems you contribute to
• Partner with product and data science teams to deliver impactful solutions
• Contribute to code reviews, documentation, and knowledge sharing across the team
• Stay current with evolving web technologies, anti-crawling mechanisms, and AI-powered extraction approaches

Must-Have Qualifications

We're prioritizing strong software engineering fundamentals over deep crawling-specific experience. The right candidate is a great engineer first; the domain can be learned on the team.

Software Engineering Fundamentals

• 5+ years of professional software engineering experience building production systems
• Strong CS fundamentals: algorithms, data structures, concurrency, distributed systems
• Proficiency in Java and/or Python
• Track record of owning features end-to-end from design through deployment and operation
• Comfortable making sound architectural decisions at the component level

Data Engineering

• Hands-on experience with cloud data warehouses such as BigQuery or Snowflake
• Experience designing and operating large-scale ETL/ELT pipelines
• Experience with orchestration tools such as Apache Airflow
• Experience with streaming or event-driven systems such as Apache Kafka

Cloud and Infrastructure

• Production experience on GCP (preferred) or AWS; multi-cloud exposure is a plus
• Hands-on experience with Kubernetes (GKE/EKS) for distributed workloads
• Familiarity with infrastructure-as-code tooling such as Terraform

Background and Mindset

• Strong communicator who can explain technical decisions clearly
• Comfortable operating in ambiguity and iterating quickly
• Bias toward action and pragmatic problem solving
• Self-starter who thrives in fast-paced, evolving environments

Nice to Have

• Experience with web crawling at scale (Scrapy or similar frameworks)
• Familiarity with proxy infrastructure, rotation strategies, or anti-bot evasion techniques
• Experience in extracting structured and unstructured web data from diverse site architectures
• Knowledge of SERP (Search Engine Results Page) extraction
• Comfort with AI/LLM-based extraction approaches, applying language models to HTML at scale
• Experience working in a B2B data company or data-as-a-product environment

Core Technical Stack

• Java and Python
• Apache Kafka
• GCP (BigQuery, GKE, Vertex AI)
• Snowflake and Starburst/Trino
• Terraform
• Scrapy and web scraping frameworks
• Proxy management systems
• Distributed systems and Kubernetes
• Apache Airflow
• Large-scale ETL pipelines

Ideal Profile

• 5+ years of software engineering experience
• Experience operating systems that process meaningful volumes of data
• Strong CS fundamentals (algorithms, data structures, distributed systems)
• Excellent communicator who can explain complex ideas to diverse audiences
• Passion for solving hard problems and building elegant, scalable systems
• Self-starter who thrives in fast-paced, evolving environments
• Experience working in a B2B data company or data-as-a-product environment is a strong plus

Why This Role Matters

This role sits at the heart of ZoomInfo's data platform. You'll contribute to the infrastructure that powers our business intelligence products and help shape how web data acquisition is done at ZoomInfo, while working at a massive scale with cutting-edge technologies.

You'll be joining at a pivotal moment: the team is growing, the ambition is high, and there's a real opportunity to make a lasting impact and grow into deeper technical leadership over time.

#LI-AR2

#LI-REMOTE

Role Description

You will be joining our Delivery Engineering team. You will work closely with the other software developers to deliver products on time and to quality while managing and communicating risks. To do this, you will design and implement new automated test frameworks (integration / system level testing rather than unit level tests), manage projects and test plans, write test tools, and have a passion for finding bugs through exploratory test methods and spotting the edge cases the developers have missed!

This role is hybrid based in Vancouver

Salary range: CA$120,000 to CA$145,000 + stock options

REQUIREMENTS

5+ years of industry experience in software development, quality engineering and/or DevOps.

Experience should include:

• Container technologies such as Docker and Kubernetes (highly desired).
• A breadth of programming languages, SDKs and test frameworks - Go (Golang) or Python experience is highly desirable.
• Defining and implementing end-to-end CI pipelines, automated test frameworks, and automated tests.
• Shell scripting, GNU makefiles, and Linux sysadmin / networking.
• Project management and team leadership.
• Having worked with many of the following: Terraform, Ansible, Jenkins, SemaphoreCI, Ginkgo, GCP, AWS, GKE, EKS, AKS, Rancher, and OpenShift.

About Your Role

We are looking for passionate and skilled software engineers to join us in our mission to secure the next generation of cloud-native applications. At the heart of our strategy is a set of open-source networking and security projects that define the new gold standard for application connectivity within large-scale cloud environments, such as Kubernetes, Docker, and related technologies. Building upon this open-source foundation, we are working on complementary commercial offerings to help enterprises build and operate cloud-native applications and infrastructures, securely and at scale.

You will be joining a team that is highly engineering-focused with a culture that values diversity, collaboration, agility, and innovation, keeping us one step ahead in the exciting and fast moving cloud-native technology space.

For this role, we are looking to hire in Vancouver (Hybrid).

Vancouver Salary Range: CAD $125,000 to CAD $150,000

Salary Range: 

You Will

• Be an active member of an engineering team working on tasks as part of release sprints
• Enhance and build new functionality in Golang
• Take responsibility (along with the team) for the entire development process of the features you are working on, including design, coding, testing, and releasing to production

You Have

5+ years of product-oriented software engineering experience

• Experience with distributed systems development
• Experience with one or more of the following areas and technologies: Kubernetes, Docker/containers, Networking.
• Hands-on experience with backend development languages like Golang (preferred), C, C++, Java, Kotlin, Python, etc.
• A drive to get things done in a highly collaborative, agile development environment
• A BS in CS or related/similar degree (equivalent experience may suffice)

Nice-to-Have

• Past experience with using storage technologies such as MongoDB or Elasticsearch.
• Any knowledge around prometheus and grafana.
• Any experience with GitOps methodologies and ArgoCD.
• Experience developing, securing, or operating cloud-scale applications or infrastructure.
• Ability to travel occasionally to attend conferences and to work with partners, customers, and colleagues in other offices

Engineering at Brex

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

As a Security Operations Engineer at Brex, you will focus on preventing, detecting and responding to security threats across Brex's corporate and cloud environments. You will use existing systems and develop tools to improve our security capabilities. Our team is responsible for functions across corporate security, detection & response and infrastructure security domains; and we perform systems engineering and automation to support those functions. 

Security Operations is part of our wider Trust & IT organization which means you will have the opportunity to work closely with Application Security, Corporate Engineering, GRC and IT and to improve security configurations, drive positive employee behaviors and generally work to prevent events from becoming incidents. You will also help build and maintain our team’s open source project Substation and have the opportunity to contribute to the Brex Tech Blog. You’ll be part of a team that actively contributes to the wider security community and has a commitment to mentorship and engineering excellence.

We’re looking for individuals with a strong background and interest in detecting, responding to, and resolving security incidents and security challenges. You should be comfortable dealing with lots of moving pieces, changing priorities, and new technologies, while having a keen eye for detail. Most importantly, you should be enthusiastic about working with a variety of backgrounds, roles, and people across Brex. Building a world-class financial service requires world-class security.

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

• Work on a highly cross-functional team to prevent, detect and respond to security threats across Brex's corporate and cloud environments
• Perform security incident response, investigation, remediation, and documentation, participate in periodic threat hunting and security exercises
• Leading, scoping and building features, participate in designing, and maintaining tools and systems which support the team’s domains – corporate security, detection & response and infrastructure security 
• Collaborating and partnering with engineering and operations teams to drive remediation of security issues, while balancing prioritization of those security issues within SLA and teams’ respective backlogs
• Caring about secure system design, valuing building things correctly, an understanding of a MVP approach and an empathetic mindset when working with others

Requirements

• Bachelor’s degree in Computer Science, Engineering or related field OR equivalent training / fellowship OR 5+ years work experienceExperience working in a corporate security, detection & response or infrastructure security role with responsibilities for security alert triage and security incident response 
• Familiarity with CI/CD systems and DevOps workflows (e.g. Buildkite, Flux, Git, Terraform) in cloud environments (e.g. AWS, Azure, GCP)
• Experience with deploying and maintaining some of the security services and tools owned by the team (e.g. - SIEM, data pipelines, SOAR, domain monitoring, endpoint tooling, email protection tooling, cloud security tools)
• While not primarily a development role, the team develops and maintains tools written in Go and Python, so experience with coding is required
• You thrive in a collaborative environment filled with a diverse group of people with different expertise and backgrounds. We currently have around 30 nationalities represented with more than ½ the company working in a country different from the one they grew up in.

Bonus points

• Proficiency with Go and other programming languages 
• Experience with securing distributed systems in AWS, cloud and Kubernetes environments
• Contributions to the wider technical community (open source, public research, mentorship, community organizing, blogging, presentations, etc)

Compensation

The expected salary range for this role is $192,000 CAD - $240,000 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.

Engineering at Brex

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

As a Security Operations Engineer at Brex, you will focus on preventing, detecting and responding to security threats across Brex's corporate and cloud environments. You will use existing systems and develop tools to improve our security capabilities. Our team is responsible for functions across corporate security, detection & response and infrastructure security domains; and we perform systems engineering and automation to support those functions. 

Security Operations is part of our wider Trust & IT organization which means you will have the opportunity to work closely with Application Security, Corporate Engineering, GRC and IT and to improve security configurations, drive positive employee behaviors and generally work to prevent events from becoming incidents. You will also help build and maintain our team’s open source project Substation and have the opportunity to contribute to the Brex Tech Blog. You’ll be part of a team that actively contributes to the wider security community and has a commitment to mentorship and engineering excellence.

We’re looking for individuals with a strong background and interest in detecting, responding to, and resolving security incidents and security challenges. You should be comfortable dealing with lots of moving pieces, changing priorities, and new technologies, while having a keen eye for detail. Most importantly, you should be enthusiastic about working with a variety of backgrounds, roles, and people across Brex. Building a world-class financial service requires world-class security.

Where you’ll work

This role will be based in our Seattle 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

• Work on a highly cross-functional team to prevent, detect and respond to security threats across Brex's corporate and cloud environments
• Perform security incident response, investigation, remediation, and documentation, participate in periodic threat hunting and security exercises
• Leading, scoping and building features, participate in designing, and maintaining tools and systems which support the team’s domains – corporate security, detection & response and infrastructure security 
• Collaborating and partnering with engineering and operations teams to drive remediation of security issues, while balancing prioritization of those security issues within SLA and teams’ respective backlogs
• Caring about secure system design, valuing building things correctly, an understanding of a MVP approach and an empathetic mindset when working with others

Requirements

• Bachelor’s degree in Computer Science, Engineering or related field OR equivalent training / fellowship OR 5+ years work experienceExperience working in a corporate security, detection & response or infrastructure security role with responsibilities for security alert triage and security incident response 
• Familiarity with CI/CD systems and DevOps workflows (e.g. Buildkite, Flux, Git, Terraform) in cloud environments (e.g. AWS, Azure, GCP)
• Experience with deploying and maintaining some of the security services and tools owned by the team (e.g. - SIEM, data pipelines, SOAR, domain monitoring, endpoint tooling, email protection tooling, cloud security tools)
• While not primarily a development role, the team develops and maintains tools written in Go and Python, so experience with coding is required
• You thrive in a collaborative environment filled with a diverse group of people with different expertise and backgrounds. We currently have around 30 nationalities represented with more than ½ the company working in a country different from the one they grew up in.

Bonus points

• Proficiency with Go and other programming languages 
• Experience with securing distributed systems in AWS, cloud and Kubernetes environments
• Contributions to the wider technical community (open source, public research, mentorship, community organizing, blogging, presentations, etc)

Compensation

The expected salary range for this role is $192,000 - $240,000. 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.

Engineering at Brex

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

As a Security Operations Engineer at Brex, you will focus on preventing, detecting and responding to security threats across Brex's corporate and cloud environments. You will use existing systems and develop tools to improve our security capabilities. Our team is responsible for functions across corporate security, detection & response and infrastructure security domains; and we perform systems engineering and automation to support those functions. 

Security Operations is part of our wider Trust & IT organization which means you will have the opportunity to work closely with Application Security, Corporate Engineering, GRC and IT and to improve security configurations, drive positive employee behaviors and generally work to prevent events from becoming incidents. You will also help build and maintain our team’s open source project Substation and have the opportunity to contribute to the Brex Tech Blog. You’ll be part of a team that actively contributes to the wider security community and has a commitment to mentorship and engineering excellence.

We’re looking for individuals with a strong background and interest in detecting, responding to, and resolving security incidents and security challenges. You should be comfortable dealing with lots of moving pieces, changing priorities, and new technologies, while having a keen eye for detail. Most importantly, you should be enthusiastic about working with a variety of backgrounds, roles, and people across Brex. Building a world-class financial service requires world-class security.

Where you’ll work

This role will be based in our New York 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

• Work on a highly cross-functional team to prevent, detect and respond to security threats across Brex's corporate and cloud environments
• Perform security incident response, investigation, remediation, and documentation, participate in periodic threat hunting and security exercises
• Leading, scoping and building features, participate in designing, and maintaining tools and systems which support the team’s domains – corporate security, detection & response and infrastructure security 
• Collaborating and partnering with engineering and operations teams to drive remediation of security issues, while balancing prioritization of those security issues within SLA and teams’ respective backlogs
• Caring about secure system design, valuing building things correctly, an understanding of a MVP approach and an empathetic mindset when working with others

Requirements

• Bachelor’s degree in Computer Science, Engineering or related field OR equivalent training / fellowship OR 5+ years work experienceExperience working in a corporate security, detection & response or infrastructure security role with responsibilities for security alert triage and security incident response 
• Familiarity with CI/CD systems and DevOps workflows (e.g. Buildkite, Flux, Git, Terraform) in cloud environments (e.g. AWS, Azure, GCP)
• Experience with deploying and maintaining some of the security services and tools owned by the team (e.g. - SIEM, data pipelines, SOAR, domain monitoring, endpoint tooling, email protection tooling, cloud security tools)
• While not primarily a development role, the team develops and maintains tools written in Go and Python, so experience with coding is required
• You thrive in a collaborative environment filled with a diverse group of people with different expertise and backgrounds. We currently have around 30 nationalities represented with more than ½ the company working in a country different from the one they grew up in.

Bonus points

• Proficiency with Go and other programming languages 
• Experience with securing distributed systems in AWS, cloud and Kubernetes environments
• Contributions to the wider technical community (open source, public research, mentorship, community organizing, blogging, presentations, etc)

Compensation

The expected salary range for this role is $192,000 - $240,000. 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.

As Marqeta’s Principal Software Engineer on the Core Issuing & Processing team, you will work across the entire domain to stand up and drive high-impact projects for our customers from inception to completion. You will take on highly technical initiatives that optimize our issuing and processing engines, own the technical roadmap for the core platform, and partner with engineering leaders to drive engineering and operational excellence throughout the organization.

We work Flexible First. This role can be performed remotely anywhere within Ontario or British Columbia, Canada. We’d love for you to join

The Core Issuing and Processing team owns the foundational stack that powers Marqeta's core business. We develop and maintain the systems that span six critical domains: Onboarding, Issuing, Digital Wallets, Authorization & Clearing, Transaction Controls, and Ledger. Together, these systems form the backbone of Marqeta's card issuing and payment processing platform.

The Impact You’ll Have

• Own the technical roadmap and author system designs that enable scalable, secure, and operationally efficient card issuing and payment processing products for our customers.
• Spend significant time in the codebase – writing, reviewing, and optimizing code across the issuing and processing stack.
• Identify and drive high-impact technical initiatives that improve the performance, reliability, and cost-efficiency of our core processing engines.
• Collaborate with Product Managers to analyze requirements and provide technical recommendations across onboarding, issuing, digital wallets, authorization & clearing, transaction controls, and ledger.
• Mentor and guide technical leads, influence stakeholders, and establish success metrics to drive organization-wide technical excellence.
• Apply and evangelize modern best practices in your software designs and implementations to increase the platform's resiliency and scalability.

Who You Are

• 12+ years of hands-on software engineering experience.
• Demonstrated passion for software engineering excellence, including design principles, fault tolerance practices, scalability, cost, security & privacy considerations, and test-driven development.
• Experience partnering with product teams to ideate and bring innovative solutions to market.
• Experience developing and scaling microservices using modern cloud technologies, preferably AWS.
• Experience working with high volume / low latency data infrastructures.
• Solid understanding of security engineering best practices and demonstrable experience in designing solutions that adhere to those standards.
• Passion for non-functional challenges, namely: Scale, Cost, Reliability, Performance, High Availability.
• Experience building systems running in multiple regions.
• Team-oriented approach – can effectively lead a project, participate as an influential team member, and work cross-functionally with other organizations.
• Experience with our tech stack, namely Java, Springboot, Kubernetes, Terraform, Helm, Kafka, JPOS, and AWS services.
  
  

Nice-To-Haves

• Master's degree in Software Engineering.
• Experience in payment processing, card issuing, or the payments industry.
• Domain experience in authorization, clearing, settlement, tokenization, or ledger systems.

Your Manager

• Arash Afrooze, Sr Director, Software Engineering

Recruiter For This Role

• Prashant

Typical Process

• Application Submission
• Recruiter phone call
• Hiring manager video call
• Virtual “Onsite” consisting of 4-5, 45 min calls

Compensation and Benefits

Marqeta is a Flex First company which allows you to choose your best working environment, whether that be from home or at a company office. To support Flex First, we calibrate pay to a competitive value according to working location. 

When determining salaries, we consider several factors including, but not limited to, skills, prior experience, and work location. The new-hire base salary range for this position, reflected in CAD,  is: 207,600 - 259,500

We also believe in recognizing the contributions of our people. That's why we award annual bonuses to eligible employees, rewarding both individual performance and the success of the entire company.

Along with monetary compensation, Marqeta offers

• Multiple health insurance options
• Flexible vacation time
• Retirement savings program with company contribution
• Equity in a publicly-traded company 
• Monthly stipend to support our remote work model
• Annual “development dollars” to support our people growth and development
• Family-forming benefits and up to 20 weeks of Parental Leave

Marqeta is looking for talented Senior Backend Software Engineers to join our Engineering team. As a Senior Software Engineer, you will develop scalable software that powers Marqeta's backend services. You will create and review engineering design documentation, continuously improve our systems, infrastructure, and processes, create features, review code, and collaborate with a diverse set of stakeholders across the company. As a Backend Engineer, you'll ship products that matter and play an important role in helping Marqeta scale as the leader in modern card issuing. You'll innovate on architecture, write impactful software and spend time mentoring other engineers. 

At Marqeta, participation in a rotational on-call pager duty is a required part of the software engineering role. The specifics of the rotation may vary by team, depending on team size and structure, and will be discussed further during the interview process.

We work Flexible First. This role can be performed remotely anywhere within Ontario or British Columbia, Canada. We’d love for you to join us!

This posting is for multiple Senior Software Engineering roles across Marqeta.

The Impact You'll Have

• Define and deliver well-scoped milestones for projects and may be a technical lead for projects on your team. 
• Actively keep customer needs in mind and leverage input from product stakeholders to determine the right technical solutions to deliver customer value quickly.
• Actively level up less-experienced members of your team by helping them with their craft, providing guidance, and setting a good example. 
• Independently write code that is clear with minimal bugs that captures the essential nature of the solution and is appropriately flexible, reusable, efficient, and adaptable to changing requirements. 
• Identify gaps and propose plans towards addressing those gaps. 
• Challenge the status quo and come up with innovative ideas.
• Lead design for small-medium components/features and participate in design for larger components/features (moving from task level impact to small-medium project level impact).
• Have significant ownership of a component/feature of the system.
• Independently design software components in well scoped scenarios, with simplicity and maintenance as key considerations, ensuring components are testable, debuggable and have logical APIs that are not easily misused.
• Participate in on-call coverage

Who You Are 

• 5+ years of experience as a backend engineer with a Bachelor’s degree; or 3 years of experience with an advanced degree.  In lieu of a degree, 8+ years of relevant experience may suffice.
• Experience building scalable software platforms.
• Experience developing in Java.
• Experience working within Cloud environments, AWS preferred.
• Experience with SQL.
• Experience with Microservices architecture. 
• Experience working with distributed systems. 
• Experience making technical trade offs and navigating technical complexities.
• Experience troubleshooting production issues.
• Ability to decompose business problems into solutions that may require designs with multiple interacting components. 
• Ability to to build correct, maintainable software components.
• A focus on quality and meeting deadlines.
• Ability to present clear and concise messages tailored to various audiences; able to communicate in a clear, concise, and respectful manner both verbally and in writing.
• Ability to share relevant information including if difficult task-level trade-offs that impact the product need to be made. 
• Ability to work with cross-functional stakeholders to identify technical blindspots and clarify ambiguity.

Nice to haves

• Experience with payments or the FinTech space
• Experience with AWS technologies 
• Experience in software delivery pipelines, CI/CD systems, and software deployment and orchestration systems such as Kubernetes and/or Docker
• Contributions to technical blogs, a public Github repo, or to open source projects
• Experience with unit testing / functional testing / integration testing
• Experience building scalable software platforms.
• Experience in end-to-end service ownership model including maintenance of infrastructure and familiarity with IaC technologies, CI/CD and observability tools (ie DataDog)

Our (typical) process:

1. Application submission
2. Recruiter video call
3. Coding interview
4. 45 min Hiring Manager video call 
5. Virtual “Onsite” consisting of three 45-60 minute rounds
6. Offer!

This position is for an existing vacancy.

Compensation and Benefits

Marqeta is a Flex First company which allows you to choose your best working environment, whether that be from home or at a company office. To support Flex First, we calibrate pay to a competitive value according to working location. 

When determining salaries, we consider several factors including, but not limited to, skills, prior experience, and work location. The new-hire base salary range for this position, reflected in CAD, is: 116,000 - 145,000.

We also believe in recognizing the contributions of our people. That's why we award annual bonuses to eligible employees, rewarding both individual performance and the success of the entire company.

Along with monetary compensation, Marqeta offers

• Multiple health insurance options
• Flexible vacation time
• Retirement savings program with company contribution
• Equity in a publicly-traded company 
• Monthly stipend to support our remote work model
• Annual “development dollars” to support our people growth and development
• Family-forming benefits and up to 20 weeks of Parental Leave

We are seeking a high-performing Enterprise Account Executive with a "hunter" mentality to drive enterprise-level growth. You will be responsible for the end-to-end sales lifecycle, from initial outbound prospecting to complex technical negotiations and final contracting. This role requires a deep understanding of Cloud Native technologies and the ability to navigate multi-stakeholder environments within the Fortune 500.

This role is hybrid based in Vancouver, BC.

Key Responsibilities:

• Full-Cycle Ownership: Chaperone opportunities from cold outreach and intro presentations through technical evaluations to final procurement.
• Strategic Prospecting: Build and execute a territory plan using a modern stack (LinkedIn SalesNav, Gong, Reo.dev, Lusha) to maintain a robust pipeline.
• Value Alignment: Translate complex technical pain points into clear value propositions, specifically aligning Tigera’s security solutions with prospect needs.
• Executive Navigation: Confidently negotiate with technical architects, Platform Directors, and C-Suite executives.
• Cross-Functional Collaboration: Partner with Finance and Legal for deal execution while simultaneously managing the technical sales motion with engineers.

Qualifications & Skills

• Experience: 5+ years of outside sales experience, specifically managing complex, multi-stakeholder enterprise deals.
• Sales Rigor: Expert-level application of the MEDDPICC methodology.
• Technical Literacy: 
  • Deep knowledge of Cloud Native Technologies & Security.
  • Familiarity with OCP, SUSE, Azure, AWS, GCP, Mirantis, and VMware, and related cloud-native security tools.
  • Existing contacts of cloud, enterprise, and architectural decision makers at NA Enterprises.
  • Bonus: Knowledge of AI/Agentic governance, security, and infrastructure.
• Proven Track Record: A documented history of exceptional quota attainment in a startup or high-growth environment.
• Adaptability: Proven ability to operate effectively in both direct and partner-led sales motions.

Why You’ll Succeed

You thrive in the "grey area" of a startup environment. You are comfortable selling highly technical, complex solutions and don't shy away from the technical grit required to win over a Cloud Architect, yet you possess the polish to close a deal with a CFO.

It all started with an idea at Block in 2013. Initially built to take the pain out of peer-to-peer payments, Cash App has gone from a simple product with a single purpose to a dynamic ecosystem, developing unique financial products, including Afterpay/Clearpay, to provide a better way to send, spend, invest, borrow and save to our 50+ million monthly active customers. We want to redefine the world's relationship with money to make it more relatable, instantly available, and universally accessible.

Today, Cash App has thousands of employees working globally across office and remote locations, with a culture geared toward innovation, collaboration and impact. We've been a distributed team since day one, and many of our roles can be done remotely from the countries where Cash App operates. No matter the location, we tailor our experience to ensure our employees are creative, productive, and happy.

The Role

On Cash App's Controls team, we build essential platform infrastructure that protects millions of Cash App customers while ensuring fair and equitable access to financial services. We partner across engineering, product, and risk teams to build highly-available infrastructure that powers critical trust and safety decisions throughout Cash App's ecosystem. We are an AI-driven engineering team — we use agentic coding tools across our entire development lifecycle, from design exploration through implementation and review, and we expect every engineer to do the same. In this role, you'll implement scalable solutions that enable billions of safe customer interactions that create a holistic experience that fosters the trust, safety, security, and support of our customers and their assets, directly contributing to Block's mission of economic empowerment through accessible and secure financial services.

You Will

• Partner closely with product managers, designers, engineers, and business leads to scope, plan, design, build, and launch new features as well as maintain existing functionality of our product controls ecosystem
• Lead technical discussions within your team and contribute to design and product discussions with partners across the organization
• Leverage your experience and knowledge to grow your teammates' technical breadth and depth through mentoring
• Direct AI agents across the full development lifecycle — from prototyping and implementation to debugging and code review — operating as the architect and decision-maker while AI handles the building
• Expand what's possible with AI tooling — identify opportunities to automate repetitive work, improve code quality through AI-driven review, and share effective patterns with your team

You Have

• 6+ years experience building and operating highly available services
• Experience contributing to cross-functional technical efforts and coordinating across teams
• Strong collaboration skills and customer empathy
• A growth mindset and comfort navigating open-ended problems
• Well-developed curiosity and initiative to build creative solutions to complex problems
• Contributed to the growth of fellow engineers through technical leadership and mentoring
• Demonstrated fluency with AI-assisted development tools (e.g., Claude Code, Cursor, GitHub Copilot, or similar agentic coding tools) in real production work — not just familiarity, but regular, effective use
• You stay current on the rapidly evolving landscape of AI tooling and actively experiment with new capabilities as they emerge

Technologies We Use and Teach

• AI-Driven Development: Claude Code, Goose (Block's open-source AI agent), Cursor, GitHub Copilot, Anthropic's Model Context Protocol (MCP)
• Kotlin, Java
• HTTP, JSON, gRPC, Protocol Buffers
• DynamoDB, MySQL
• Event-driven architecture (Kafka)
• DataDog, Prometheus
• AWS, Kubernetes

We’re working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Block is an equal opportunity employer evaluating all employees and job applicants without regard to identity or any legally protected class. We also consider qualified applicants with criminal histories for employment on our team, and always assess candidates on an individualized basis. We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations throughout the recruitment process. If you require an accommodation, let your recruiter know.  Want to learn more about what we’re doing to build an inclusive workplace? Check out our Inclusion & Diversity page.

Databricks is on a mission to simplify and democratize data and AI — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

As a Fullstack software engineer, you will work with your team and product management to make insights from data simple. We are looking for engineers that are customer obsessed, who can take on the full scope of the product and user experience beyond the technical implementation. You'll set the foundation for how we build robust, scalable and delightful products.

Vancouver will be the newest R&D center for Databricks, expanding our presence in the Pacific Northwest. We are actively hiring world-class engineers to join us on our mission to democratize data + AI.  

We envision the Vancouver site becoming a key driver of product innovation at Databricks. To start, we’re bringing a few strategic areas to the Vancouver site and we have several open roles across the teams below, including:

• Log Analytics - Our customers increasingly use Databricks to analyze petabyte-scale logs in real time. This creates new challenges across the entire data processing pipeline, including ingestion, indexing, processing, and the user experience itself.
• AI/BI - AI/BI is redefining Business Intelligence for the AI age. We launched this product last summer and have already seen tremendous adoption (98.7% of our data warehousing customers are already using AI/BI!). From rich dashboarding and advanced visualizations to powerful talk-to-your-data solutions, the products we are building involve exciting technical challenges across the entire stack. 
• Unity Catalog Business Semantics - Context is everything for AI. For enterprise data, that context needs to be governed and managed, which is what Unity Catalog Business Semantics offers. We recently launched our first Semantics modelling capability, Unity Catalog Metrics, this past Data + AI Summit but we have a lot more in store. Engineers on this team work at the intersection of large scale distributed systems, data modeling, governance, and AI enablement.
• Databricks Apps - Databricks Apps is one of the fastest growing products at Databricks, used by more than 2,500 customers who have created more than 20,000 apps — and it was only GA’ed this past June. The Apps team is one of the few teams that are exposed to low-level platform components (k8s, networking), owns fundamental tech (apps runtime and proxy), and is heavily investing in app builder AI agents.

What we look for:

• 5+ years of experience with HTML, CSS, and JavaScript.
• Passion for user experience and design and a deep understanding of front-end architecture.
• Comfortable working towards a multi-year vision with incremental deliverables.
• Motivated by delivering customer value.
• Experience with modern JavaScript frameworks (e.g., React, Angular, or VueJs/Ember).
• 5+ years of experience with server-side web technologies (eg: Node.js, Java, Python, Scala, C#, C++,Go).
• Good knowledge of SQL.
• Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, or Kubernetes.
• Experience developing large-scale distributed systems.

At Databricks, we’re passionate about enabling data teams to solve the world’s toughest problems — from accelerating medical breakthroughs to building the next generation of intelligent products. We do this by creating the world’s best Data Intelligence Platform, empowering customers to turn massive data into deep, actionable insights.

Founded by engineers and driven by innovation, we’re obsessed with designing intuitive, high-performance user experiences that make complex data exploration simple and approachable.

As a Senior Frontend Engineer focused on Dashboards, you’ll build intuitive and scalable end-to-end experiences that help users create, explore, and share insights from data. You’ll work across the frontend, partnering with designers, product managers, and engineers to develop the next generation of dashboards, interactivity, and analytical workflows within Databricks.

What You’ll Do

• Design and build intuitive, high-performance experiences for creating and editing dashboards, as well as for authoring the data behind them, including SQL datasets, custom calculations, and semantic modeling.
• Partner closely with design and product to translate complex analytical concepts into polished, intuitive, and efficient dashboard experiences.
• Drive innovation in how Databricks users interact with data, enabling seamless and responsive exploration at scale.
• Own frontend development for core dashboard workflows, with a focus on usability, performance, accessibility, and reliability.
• Help shape the architecture, abstractions, and platform foundations that support a broad range of dashboarding and analytical use cases.
• Collaborate with backend engineers and adjacent teams to define APIs, data models, and contracts that power interactive and scalable dashboard experiences.

What We Look For

• 5+ years of professional software engineering experience, with strong experience building both frontend and backend systems.
• Expertise in modern frontend development with HTML, CSS, JavaScript/TypeScript, and React, or similar frameworks.
• Deep understanding of UX principles, accessibility, and responsive design for data-heavy interfaces.
• Experience designing scalable systems and abstractions that support interactive, high-performance product experiences.
• Proven ability to collaborate cross-functionally and deliver impactful user-facing features.
• Experience building dashboards, analytics, data exploration, authoring tools, or business intelligence products is a plus.
• Familiarity with SQL authoring, custom calculations, semantic modeling, or related analytical workflows is a plus.
• Experience with cloud technologies such as AWS, Azure, GCP, or Kubernetes is preferred.

Lantern is seeking an experienced Senior Cloud Platform Engineer to drive the evolution of our Azure-based infrastructure, focusing on scalability, automation, and regulatory compliance. In this pivotal role, you will architect, implement, and operate a secure, resilient, multi-region cloud platform that supports our mission to make excellent, affordable care more accessible to everyone.

You will collaborate with a talented team of cloud engineers and architects, championing operational excellence and delivering highly available, HIPAA- and SOC-compliant infrastructure. Working closely with security, application development, and business teams, you will help build robust, enterprise-grade platforms that empower innovation, agility, and growth.

This role is ideal for a cloud expert with deep Microsoft Azure expertise, a strong record of contributing to high-performing teams, and a passion for building scalable infrastructure in dynamic, fast-paced enterprise environments.

Location: Hybrid - at least 3 days/wk in Vancouver, BC
On-Call:  This position requires being on-call 1 week per month at the most

Responsibilities:

• Design, implement, and maintain secure, scalable, and highly available Azure cloud infrastructure to support Lantern’s healthcare solutions.
• Collaborate with cloud architects, engineers, application developers, and InfoSec teams to deliver enterprise-grade cloud platforms that meet HIPAA, SOC 2, and other regulatory requirements.
• Develop and maintain Infrastructure-as-Code (IaC) using tools such as Terraform to automate provisioning, configuration, and deployment of Azure resources.
• Implement and optimize CI/CD pipelines using Azure DevOps and GitHub Actions to support agile software development and rapid release cycles.
• Ensure robust monitoring, observability, and alerting for production systems; proactively address incidents and contribute to incident response.
• Participate in cost optimization efforts by monitoring resource usage and recommending efficiencies for cloud spend.
• Contribute to disaster recovery planning, business continuity, and uptime strategies for critical healthcare applications.
• Maintain comprehensive documentation for infrastructure, deployments, and operational procedures.
• Participate in cross-functional meetings with product, engineering, and compliance teams to ensure infrastructure aligns with business and regulatory goals.
• Mentor junior engineers and support a culture of collaboration and continuous improvement within the team.

 Requirements:

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field, or equivalent practical experience.
• 4+ years of experience in cloud infrastructure engineering, systems administration, or DevOps roles.
• 3+ years of hands-on experience with Microsoft Azure (experience with AWS or Google Cloud Platform is a plus).
• Experience designing, deploying, and managing cloud-based infrastructure at scale.
• Practical experience configuring and maintaining CI/CD pipelines using Azure DevOps and GitHub Actions.
• Proven experience in a regulated environment, ideally in the healthcare sector with HIPAA and/or SOC compliance requirements.
• Hands-on exposure to security best practices for cloud environments, including identity and access management, encryption, and monitoring/logging.
• Strong problem-solving and troubleshooting abilities.
• Excellent communication and collaboration skills.
• If you don’t meet every requirement listed, we still encourage you to apply.

Strong Candidates Will: 

• Strong experience with Infrastructure as Code (IaC), especially Terraform, to automate Azure resources.
• Experience managing Azure App Services, networking, and storage solutions.
• Experience with containerization (Docker, Azure Kubernetes Service) is a plus.
• Relevant Azure certifications (e.g., Azure Solutions Architect, Azure Administrator) are a plus.

Benefits: 

• Medical Insurance
• Dental Insurance
• Vision Insurance
• Short- & Long-Term Disability
• Life Insurance
• RRSP with company match

About Your Role

As a Senior TestOps Engineer within our Delivery Engineering team, you will be the architect of our quality gates. You won't just be "testing" software,  you will be building the high performance infrastructure and automated tooling that allows our developers to ship code with confidence and speed. You will bridge the gap between QA, DevOps, and Software Engineering to ensure our delivery pipeline is resilient, observable, and scalable.

This role is hybrid based in Vancouver

Salary range: CA$125,000 to CA$150,000 + stock options

You Will 

• Architect Test Infrastructure: Design and implement ephemeral test environments and automation frameworks for the various Kubernetes platforms in different Clouds using Golang, Docker/Kubernetes, and Terraform/Pulumi.
• Eliminate Toil: Identify manual bottlenecks in the delivery process and write automated tools and solutions to replace them using Golang.
• Gap Analysis and Strategy: Proactively identify architectural blind spots in complex integration points and write robust automated test suites using Go-test and Ginkgo, ensuring high-concurrency and flake-resistant execution.
• Engineer CI Pipelines: Build and maintain sophisticated CI/CD workflows (GitHub Actions, Tekton) that integrate automated testing seamlessly into the development lifecycle.
• Observability Integration: Work with OpenTelemetry, Elasticsearch, and Kibana to ensure test results provide deep, actionable insights into system health.
• Support Release delivery: Lead the creation of comprehensive release test plans, managing risk communication across Product and Engineering stakeholders.
• Champion Exploratory Testing: Beyond automation, apply a "breaker" mindset to uncover edge cases through exploratory testing and performance benchmarking.

You Have

• Experience: 5+ years in Software Test Tooling, DevOps, or Site Reliability Engineering (SRE).
• The "Engineer’s Engineer": Strong development skills in Go or Python. We need someone who doesn’t just use tools but builds them. Has a deep-seated drive to improve the developer experience by creating seamless, automated guardrails. A wide majority of our tools are built in-house.
• IaC Mindset: Experience treating infrastructure as a software problem (eg. Terraform, Pulumi) and believes environments should be as ephemeral and versioned as the code itself.
• Cloud & Containers: Comfortable navigating the complexities of K8s, from managing container lifecycles in Docker to troubleshooting pod lifecycles and resource usage in AWS/GCP/Azure.
• Quality Strategists: Who don’t just "run tests"; they identify coverage gaps at the architectural level. Have the foresight to pinpoint where service boundaries might fail and possess the skill to automate the validation of those integration points.
• CI/CD Architects: A star designing high performance pipelines (e.g., GitHub Actions, Tekton) that provide fast, reliable feedback loops to engineering teams.
• Observability Advocates: Believes that testing doesn't end at "Pass/Fail." And are looking for ways to integrate OpenTelemetry, Elastic, or Kibana to gain deep insights into system reliability via test performance.

Nice-to-Have

• Platform Mastery: Experience with Kubernetes distributions like OpenShift, Rancher, MKE.
• Hybrid Cloud: Familiarity with virtualization (vSphere, KubeVirt).
• The Logging Stack: Hands-on experience with Log aggregation (ElasticSearch/OpenSearch).
• Observability: Experience with distributed tracing (OpenTelemetry) and complex performance profiling.

Sony Pictures Imageworks is located on the unceded traditional territory of the Musqueam, Squamish, and Tsleil-Waututh First Nations. We are committed to respecting traditional lands, and working with communities towards reconciliation.

Sony Pictures Imageworks Canada Inc.

658 Homer Street., Suite 405, Vancouver, BC, V6B 2R4

Project based, Full Time

Language in work environment - English

Benefits per company policy: include healthcare, tuition reimbursement, RRSP's, Sick and Vacation leave, standard increases as applicable

JOB SUMMARY
We are seeking a skilled DevOps Engineer to join our technology team supporting global content production, post-production, and distribution workflows. The ideal candidate will have a strong background in cloud infrastructure automation, scalable deployment architectures, and Kubernetes cluster management. You will be working closely with our engineering, media operations, and security teams to ensure our platforms can scale dynamically to meet the needs of high-traffic media pipelines and digital distribution systems.

EDUCATION, QUALIFICATIONS AND EXPERIENCE

FORMAL EDUCATION
● Bachelor’s degree, with a preference for Computer Science, Engineering or other technical degree.

PRIMARY AREAS OF RESPONSIBILITY WILL INCLUDE:
● Manage and optimize multi-cluster Kubernetes environments across AWS, GCP, or Azure.
● Implement autoscaling policies and node management strategies for high-availability workloads.

● Maintain service mesh configurations (e.g., Istio or Linkerd) and monitor cluster health.
● Design and maintain infrastructure-as-code (IaC) with Terraform, Helm, or CloudFormation.
● Build and manage automated CI/CD pipelines using GitHub Actions, Jenkins, or GitLab CI.
● Implement and optimize horizontal/vertical scaling for microservices and API workloads.
● Support serverless and hybrid-cloud architectures where applicable.
● Automate routine operational tasks, deployments, and environment provisioning.
● Set up and maintain monitoring, logging, and alerting systems using tools like Zabbix, Grafana, Pagerduty, ELK, or Datadog.
● Continuously improve system reliability and deployment velocity.
● Partner with development teams to containerize applications and ensure production readiness.
● Collaborate with security teams to enforce compliance, patch management, and secrets handling (Vault, AWS KMS, etc.).
● Participate in on-call rotations and post-incident reviews.

EXPERIENCE:
● 3–6 years of experience in DevOps, Site Reliability, or Cloud Engineering roles.
● Strong hands-on experience managing Kubernetes clusters in production.
● Proficiency in one or more public cloud platforms (AWS, GCP, or Azure).
● Experience with IaC tools (Terraform, Helm, or Ansible).
● Strong scripting skills (Python, Bash, or Go).
● Familiarity with containerization (Docker) and CI/CD tooling.
● Experience supporting high-throughput or media-intensive workloads.
● Knowledge of CDN integration, data pipelines, or transcoding workflows.
● Familiarity with cost optimization and cloud performance tuning.
● Exposure to zero-downtime deployment strategies and GitOps practices (ArgoCD, Flux).
● Certifications such as CKA, CKAD, or cloud-specific equivalents.

OTHER:
● You will establish a clear understanding of the company's vision, goals and strategy and actively contribute to the achievement of the goals and execution of the strategy
● You will be a leader in the organization, responsible for both setting the standards for project management and holding the organization accountable to the standards set
● You are results-oriented with a history of consistently meeting deadlines

● You possess a proactive mindset with a focus on continuous improvement
● You possess excellent written and spoken technical English, as well as strong documentation skills
● You are capable of working with distributed teams across software, infrastructure, and content delivery, in a fast-paced, production-oriented environment

LOCATION AND WORK MODEL
● Vancouver / Hybrid — occasional on-site collaboration with studio technology and production teams.

The anticipated base salary for this position is $104,200.00 to $145,000.00/annually. This role may also qualify for annual incentive and/or comprehensive benefits per company policy: including healthcare, tuition reimbursement, RRSP's, sick and vacation leave, standard increases as applicable. The actual base salary offered will depend on a variety of factors, including without limitation, the qualifications of the individual applicant for the position, years of relevant experience, level of education attained, certifications or other professional licenses held, and if applicable, the location of the position.

We value unique perspectives, and want diverse, unique talent to work with us. We encourage candidates from all identities to apply.

Sony Pictures Entertainment is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, national origin, disability, age, sexual orientation, gender identity, or other protected characteristics.

About the Team:

Databricks is on a mission to simplify and democratize data and AI — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

As a Fullstack software engineer, you will work with your team and product management to make insights from data simple. We are looking for engineers that are customer obsessed, who can take on the full scope of the product and user experience beyond the technical implementation. You'll set the foundation for how we build robust, scalable and delightful products.

Vancouver will be the newest R&D center for Databricks, expanding our presence in the Pacific Northwest. We are actively hiring world-class engineers to join us on our mission to democratize data + AI.  

We envision the Vancouver site becoming a key driver of product innovation at Databricks. To start, we’re bringing a few strategic areas to the Vancouver site and we have several open roles across the teams below, including:

• Log Analytics - Our customers increasingly use Databricks to analyze petabyte-scale logs in real time. This creates new challenges across the entire data processing pipeline, including ingestion, indexing, processing, and the user experience itself.
• AI/BI - AI/BI is redefining Business Intelligence for the AI age. We launched this product last summer and have already seen tremendous adoption (98.7% of our data warehousing customers are already using AI/BI!). From rich dashboarding and advanced visualizations to powerful talk-to-your-data solutions, the products we are building involve exciting technical challenges across the entire stack. 
• Unity Catalog Business Semantics - Context is everything for AI. For enterprise data, that context needs to be governed and managed, which is what Unity Catalog Business Semantics offers. We recently launched our first Semantics modelling capability, Unity Catalog Metrics, this past Data + AI Summit but we have a lot more in store. Engineers on this team work at the intersection of large scale distributed systems, data modeling, governance, and AI enablement.
• Databricks Apps - Databricks Apps is one of the fastest growing products at Databricks, used by more than 2,500 customers who have created more than 20,000 apps — and it was only GA’ed this past June. The Apps team is one of the few teams that are exposed to low-level platform components (k8s, networking), owns fundamental tech (apps runtime and proxy), and is heavily investing in app builder AI agents.

What we look for:

• 10+ years of experience with HTML, CSS, and JavaScript.
• Passion for user experience and design and a deep understanding of front-end architecture.
• Comfortable working towards a multi-year vision with incremental deliverables.
• Motivated by delivering customer value.
• Experience with modern JavaScript frameworks (e.g., React, Angular, or VueJs/Ember).
• 10+ years of experience with server-side web technologies (eg: Node.js, Java, Python, Scala, C#, C++,Go).
• Good knowledge of SQL.
• Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, or Kubernetes.
• Experience developing large-scale distributed systems.

P-1440

Databricks is on a mission to simplify and democratize data and AI — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

Vancouver will be the newest R&D center for Databricks, expanding our presence in the Pacific Northwest. We are actively hiring world-class engineers to join us on our mission to democratize data + AI.  

We envision the Vancouver site becoming a key driver of product innovation at Databricks. To start, we’re bringing a few strategic areas to the Vancouver site and we have several open roles across the teams below, including:

• Log Analytics - Our customers increasingly use Databricks to analyze petabyte-scale logs in real time. This creates new challenges across the entire data processing pipeline, including ingestion, indexing, processing, and the user experience itself.
• AI/BI - AI/BI is redefining Business Intelligence for the AI age. We launched this product last summer and have already seen tremendous adoption (98.7% of our data warehousing customers are already using AI/BI!). From rich dashboarding and advanced visualizations to powerful talk-to-your-data solutions, the products we are building involve exciting technical challenges across the entire stack. 
• Unity Catalog Business Semantics - Context is everything for AI. For enterprise data, that context needs to be governed and managed, which is what Unity Catalog Business Semantics offers. We recently launched our first Semantics modelling capability, Unity Catalog Metrics, this past Data + AI Summit but we have a lot more in store. Engineers on this team work at the intersection of large scale distributed systems, data modeling, governance, and AI enablement.
• Databricks Apps - Databricks Apps is one of the fastest growing products at Databricks, used by more than 2,500 customers who have created more than 20,000 apps — and it was only GA’ed this past June. The Apps team is one of the few teams that are exposed to low-level platform components (k8s, networking), owns fundamental tech (apps runtime and proxy), and is heavily investing in app builder AI agents.

What we look for:

• BS (or higher) in Computer Science, related technical field or equivalent practical experience.
• Comfortable working towards a multi-year vision with incremental deliverables.
• Motivated by delivering customer value and impact.
• 5+ years of production level experience in either Java, Scala or C++.
• Strong foundation in algorithms and data structures and their real-world use cases.
• Experience developing large-scale distributed systems.
• Experience working on a SaaS platform or with Service-Oriented Architectures.
• Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, or Kubernetes.
• Experience with security and systems that handle sensitive data.
• Good knowledge of SQL.

Databricks is on a mission to simplify and democratize data and AI — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

Vancouver will be the newest R&D center for Databricks, expanding our presence in the Pacific Northwest. We are actively hiring world-class engineers to join us on our mission to democratize data + AI.  

We envision the Vancouver site becoming a key driver of product innovation at Databricks. To start, we’re bringing a few strategic areas to the Vancouver site and we have several open roles across the teams below, including:

• Log Analytics - Our customers increasingly use Databricks to analyze petabyte-scale logs in real time. This creates new challenges across the entire data processing pipeline, including ingestion, indexing, processing, and the user experience itself.
• AI/BI - AI/BI is redefining Business Intelligence for the AI age. We launched this product last summer and have already seen tremendous adoption (98.7% of our data warehousing customers are already using AI/BI!). From rich dashboarding and advanced visualizations to powerful talk-to-your-data solutions, the products we are building involve exciting technical challenges across the entire stack. 
• Unity Catalog Business Semantics - Context is everything for AI. For enterprise data, that context needs to be governed and managed, which is what Unity Catalog Business Semantics offers. We recently launched our first Semantics modelling capability, Unity Catalog Metrics, this past Data + AI Summit but we have a lot more in store. Engineers on this team work at the intersection of large scale distributed systems, data modeling, governance, and AI enablement.
• Databricks Apps - Databricks Apps is one of the fastest growing products at Databricks, used by more than 2,500 customers who have created more than 20,000 apps — and it was only GA’ed this past June. The Apps team is one of the few teams that are exposed to low-level platform components (k8s, networking), owns fundamental tech (apps runtime and proxy), and is heavily investing in app builder AI agents.

What we look for:

• BS (or higher) in Computer Science, related technical field or equivalent practical experience.
• Comfortable working towards a multi-year vision with incremental deliverables.
• Motivated by delivering customer value and impact.
• 10+ years of production level experience in either Java, Scala or C++.
• Strong foundation in algorithms and data structures and their real-world use cases.
• Experience developing large-scale distributed systems.
• Experience working on a SaaS platform or with Service-Oriented Architectures.
• Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, or Kubernetes.
• Experience with security and systems that handle sensitive data.
• Good knowledge of SQL.

Synthesis Health

Who We Are

We’re a mission- and values-driven company with tremendous dedication to our customers. Our 100% remote team is dedicated to a common goal – to revolutionize healthcare through innovation, collaboration, and commitment to our core values and behaviors.

About the Opportunity

We are looking for a Staff Platform Engineer to serve as the architect of our edge.

In this critical role, you will own the boundary between the world and our platform. You will own the "Customer Edge"—the mission-critical software gateways that run inside hospital networks, acting as the secure bridge for DICOM and HL7 data into our cloud platform.

You will solve unique distributed systems challenges: How do you buffer terabytes of imaging data on-premise when the hospital's internet goes down? How do you safely auto-update thousands of remote agents behind strict enterprise firewalls? How do you enforce fairness and rate limiting to prevent one tenant from degrading the experience for everyone else?

This is a hands-on leadership role. You will write high-performance code, define the architectural patterns for edge ingestion, and mentor engineers on the nuances of network reliability and secure tunneling.

Key Responsibilities

Customer Gateway Architecture & High Availability (HA)

• On-Premise Gateway Reliability: You will architect our edge gateway software to run reliably within customer data centers. You will implement HA patterns to ensure that a single hardware failure never stops critical patient data flow.
• High-Performance Ingestion: You will optimize the ingestion path for massive DICOM studies and HL7 streams. You will implement local queuing and backpressure mechanisms that protect our core platform from being overwhelmed by "thundering herds" of data when connectivity is restored after an outage.
• Versioning & Fleet Management: You will design the control plane for our distributed fleet of gateways. You will solve the "Day 2" operations challenge: architecting automated, over-the-air (OTA) update mechanisms that allow us to patch, upgrade, and version-manage thousands of remote agents without manual intervention or customer downtime.

Cloud Ingestion & Throughput Protection

• Resilient Ingestion Strategy: You will design the cloud-side ingestion layer (using technologies like Kafka or PubSub) to absorb massive bursts of traffic. You will ensure that our architecture can handle "thundering herds" from reconnected agents without dropping a single packet of patient data.
• Load Shedding & Fairness: You will implement sophisticated fairness algorithms and load shedding strategies at the ingestion point to ensure that no single customer gateway can monopolize cloud resources or degrade the performance of the broader platform.

Network & Connectivity Security

• Secure Tunnels: You will design the secure connectivity patterns (e.g., mutual TLS, reverse tunnels, VPNs) that allow our cloud to communicate with private hospital networks without requiring complex firewall exceptions.
• Mentorship: You will be the subject matter expert (SME) on networking and edge computing. You will mentor the team on TCP/IP mechanics, TLS optimization, and low-level network debugging.

What We’re Looking For

• Deep Edge & Networking Experience: 8+ years of engineering experience, with a focus on Edge Computing or Distributed Agents. You understand the physics of the internet, from TCP congestion control to TLS handshakes.
• Hybrid/On-Prem Expertise: You have shipped software that runs in customer environments (on-prem). You understand the constraints of enterprise firewalls, proxies, and limited bandwidth.
• Language Fluency: Deep expertise in Go (Golang) or TypeScript is required.
• Queuing & Streaming: Expert-level knowledge of asynchronous architectures using Google Cloud Pub/Sub, Dataflow, or Kafka. Given our GCP environment, deep proficiency with Pub/Sub and Dataflow is highly preferred. You understand backpressure and how to design for eventual consistency.
• Containerization: Experience distributing software via Docker/Kubernetes and managing container lifecycles in remote environments.

Preferred Qualifications

• Healthcare Interoperability: Deep, hands-on experience building integrations against DICOM (C-STORE, DIMSE services) or HL7 MLLP protocols. You understand the nuances of the association negotiation, transfer syntaxes, and strict acknowledgment requirements necessary to reliably accept data from legacy hospital systems.

Why You Should Join Us

• Solve Our Toughest Puzzles: This is a high-leverage role. You will be working on the most impactful technical challenges that are critical to the company's success.
• Define the Architecture: You won't just be maintaining a system; you will be a primary author of its future state, with the autonomy to make it happen.
• Lead from the Front: This is a chance to establish yourself as a key technical voice in a rapidly growing company.
• Competitive Compensation & Benefits: We offer a strong salary, a 100% remote culture, and significant opportunities for growth.

We are a values-driven company. Our values:

• Clinical service first.
• Collaborate with our customers.
• Listen, respect, learn.
• Innovate to excel.

The behaviors we look for:

• Be nice.
• Be creative.
• Be honest.
• Be helpful.

Compensation and Benefits

Typical salary range for this position is $120,000 - $150,000 (CAD). However, Synthesis participates in location based hiring and salary ranges can be adjusted based on candidate's residence. 

Other benefits include, but are not limited to: Medical, Dental, Vision, “Use as needed” vacation policy, and participation in our employee option program.

Synthesis Health

Who We Are

We’re a mission- and values-driven company with tremendous dedication to our customers. Our 100% remote team is dedicated to a common goal – to revolutionize healthcare through innovation, collaboration, and commitment to our core values and behaviors.

About the Opportunity

We are looking for an experienced Sr. Platform Engineer to help build the next generation of our cloud-native healthcare platform. You will be a key technical contributor, responsible for designing, building, and owning critical components that form the backbone of our systems. You will focus on improving the scalability, performance, and reliability of our services, enabling our product teams to deliver innovative features to our customers faster and more securely.

If you are a builder who thrives on solving complex distributed systems problems, enjoys mentoring others, and wants to make a significant impact on healthcare, this is the perfect opportunity for you.

Key Responsibilities

• Design and Build Core Platform Services: Design, develop, and maintain scalable, resilient, and secure platform components and microservices that are critical to project success and product capabilities.
• Drive Performance and Reliability: Promote and implement best practices for observability, monitoring, and performance testing. You will analyze and optimize application-level performance for our critical workflows, ensuring they meet strict uptime and speed requirements.
• Improve System Architecture: Contribute to the analysis of our platform architecture, helping to identify performance bottlenecks, improve data and caching flows, and simplify architectural complexity.
• Elevate Code Quality: Write clean, maintainable, and well-tested code for core platform services. You will set a high standard for code quality and testing within the team by leading design reviews and providing constructive feedback.
• Lead with Technical Expertise and Mentorship: Formally or informally mentor junior engineers, helping to level up the team through code reviews, knowledge sharing, and hands-on guidance. You will significantly influence your team's technical direction and decisions.
• Create Excellent Documentation: Produce clear, high-quality architectural diagrams and technical documentation for the components you own, contributing to the team's shared knowledge base.

What We’re Looking For

• Experience in Distributed Systems: 5+ years of software engineering experience with a strong track record of designing, building, and operating scalable and high-performance services.
• Strong Architectural and Design Skills: You can independently tackle complex technical challenges within your domain, architecting robust solutions and making sound technical trade-offs with minimal guidance.
• Performance and Debugging Expertise: You have hands-on experience instrumenting and debugging performance issues across a full stack—from application code and databases to caching layers and infrastructure—using modern performance profiling and monitoring tools.
• Hands-On Expertise with Modern Tech Stacks: You have practical knowledge of the principles and technologies behind our platform:
  • Microservices, event-driven design, and distributed architectures.
  • Cloud platforms (GCP preferably), with hands-on experience in Docker and Kubernetes (e.g., GKE, Cloud Run).
  • Expertise across relational and NoSQL databases (e.g., PostgreSQL/AlloyDB, MongoDB, Redis) and data warehousing (e.g., BigQuery).
  • Real-world experience with Pub/Sub messaging systems (e.g., Google Cloud Pub/Sub, Kafka).
  • Statically typed languages (e.g., TypeScript, Go, C/C++, Java, Rust).
  • Gitflow branching model.
• Clarity in Communication: You can clearly articulate complex technical ideas to both technical and non-technical stakeholders. Your diagrams and documents are a source of clarity.
• Leadership Through Influence: You have a demonstrated ability to influence your team's technical direction, driving consensus, and elevating the bar for engineering excellence.

Preferred Qualifications

• Healthcare Domain Experience: While engineering excellence is paramount, your application will stand out if you have experience in regulated industries. Deep familiarity with healthcare data standards (DICOM, HL7) and compliance regulations (HIPAA) is a significant advantage.

Why You Should Join Us

• Solve Challenging Problems: This is a high-leverage role. You will be working on impactful technical challenges that are critical to the company's success.
• Build the Future of Healthcare: You won't just be maintaining a system; you will be a primary builder of its future state, with the autonomy to own major components.
• Make a Major Impact: This is a chance to establish yourself as a key technical voice on a team that is transforming healthcare.
• Competitive Compensation & Benefits: We offer a strong salary, meaningful equity, a 100% remote culture, and significant opportunities for growth.

We are a values-driven company. Our values:

1. Clinical service first.
2. Collaborate with our customers.
3. Listen, respect, learn.
4. Innovate to excel.

The behaviors we look for:

1. Be nice.
2. Be creative.
3. Be honest.
4. Be helpful.

Compensation and Benefits

Typical salary range for this position is $85,000 - $110,000. However, Synthesis participates in location based hiring and salary ranges can be adjusted based on candidate's residence. 

Other benefits include, but are not limited to: Medical, Dental, Vision, “Use as needed” vacation policy, and participation in our employee option program.

About this position:

We’re looking for a Machine Learning Infrastructure Engineer to join our growing Data & Platform team and build the foundation that powers our AI and machine learning capabilities across Later’s product portfolio. As our first dedicated ML Infrastructure Engineer, you will own the systems that support model experimentation, training, deployment, and monitoring at scale.

This role is critical to accelerating our data science initiatives and enabling future AI innovation. You’ll design and operate reliable, secure, and scalable ML infrastructure that empowers data scientists and engineers to ship high-impact models with confidence. If you’re excited about building robust ML systems in a fast-moving environment—and want to define the standard for ML Ops at Later—this is your opportunity.

What you'll be doing:

Strategy

• Define and own the long-term ML infrastructure roadmap, ensuring it supports both current experimentation needs and future AI initiatives.
• Establish best practices for model lifecycle management, deployment standards, monitoring, and governance. 
• Identify infrastructure gaps and proactively design scalable solutions to enable high-velocity ML development.
• Contribute to cross-functional technical planning, ensuring ML systems align with product and platform strategy.

Technical/ Execution

• Design, build, and maintain production-grade model deployment and inference systems using CI/CD pipelines, containerized services (Docker), and API frameworks (e.g., Flask).
• Automate end-to-end ML lifecycle workflows including training pipelines, model validation, registry management, deployment, and rollback strategies.
• Implement robust monitoring systems for model performance, latency, drift detection, and infrastructure health using tools such as CloudWatch, Prometheus, and Grafana.
• Operate across AWS and GCP environments to manage training and inference workloads, including GPU-based infrastructure and BigQuery datasets.
• Develop and maintain infrastructure-as-code (Terraform, CloudFormation) to ensure scalable, repeatable, and secure cloud environments.
• Implement and optimize CI/CD workflows (e.g., GitHub Actions, GitLab CI, Bitbucket Pipelines) for ML and infrastructure automation.

Team / Collaboration

• Partner closely with Data Scientists, Analysts, Platform Engineers, and Product Engineers to support end-to-end ML workflows.
• Translate data science experimentation needs into production-ready infrastructure solutions.
• Serve as the technical bridge between ML experimentation and productized deployment.
• Share knowledge and best practices to elevate ML maturity across teams.

Research/Best Practices

• Stay current on emerging ML Ops practices, tools, and frameworks to continuously improve system reliability and efficiency.
• Evaluate and implement model-serving frameworks (e.g., TorchServe, Seldon, TensorRT) where appropriate.
• Contribute to governance, reproducibility, and auditability standards for ML systems.
• Experiment with new tooling and workflows to improve reproducibility, performance, and developer velocity.

What success looks like:

• ML models move from experimentation to production quickly and reliably, with minimal manual intervention.
• CI/CD pipelines enable safe, repeatable deployments with clear rollback strategies.
• Model performance, drift, and infrastructure health are proactively monitored and observable.
• Infrastructure supports scalable GPU training and real-time inference without bottlenecks.
• Data scientists report improved velocity, reproducibility, and confidence in deploying models.
• ML systems are secure, compliant, and aligned with evolving product and AI strategy.

What you bring:

• 4+ years of experience in ML Ops, ML infrastructure, backend engineering, or related roles supporting production ML systems.
• Experience working in cloud-native environments (AWS and/or GCP) with hands-on deployment of ML workloads.
• Proven track record designing and implementing CI/CD pipelines for ML systems.
• Strong experience with Amazon SageMaker, Docker, Flask-based APIs, and infrastructure automation tools.
• Hands-on experience with ML lifecycle tooling such as MLflow, SageMaker Studio, or Weights & Biases.
• Experience managing container orchestration platforms (Kubernetes, EKS, or GKE).
• Strong programming experience in Python (additional experience in Go, Java, or Scala is a plus).
• Experience working with infrastructure-as-code tools such as Terraform or CloudFormation.
• Familiarity with observability tools such as CloudWatch, Prometheus, Grafana, Datadog, or centralized logging platforms.
• Experience managing GPU-based workloads and scaling training/inference systems.
• Familiarity with data infrastructure tools such as BigQuery and cloud-native data pipelines.
• Bonus: Experience supporting LLMs or generative AI pipelines, distributed training systems, feature stores (e.g., Feast), real-time inference systems, or ML governance frameworks.
• A mindset focused on automation, reliability, performance, and continuous improvement in fast-scaling environments.

How you work: 

• Driven by Impact: You deliver results that matter—prioritizing high-value work, meeting deadlines, and adapting quickly while keeping outcomes clear.
• Strategic & Customer-Centric: You anticipate risks and opportunities, connect decisions to long-term growth, and build trust through proactive insights.
• Curious & Growth-Oriented: You seek knowledge, ask sharp questions, and apply learnings fast—challenging the status quo with a mindset of improvement.
• Collaborative & Resilient: You thrive in change by staying resourceful, solution-focused, and positive—removing roadblocks, sharing insights, and keeping morale high.
• Accountable & Honest: You own your work, hold yourself and others to a high bar, and use transparent feedback to drive growth.
• Emotionally Intelligent: You build trust through empathy and collaboration, foster inclusion, and inspire others with grit, optimism, and integrity.

Our approach to compensation:

We take a market-based & data-driven approach to compensation. We leverage data from trusted third-party compensation sources to help us understand the market value of a role based on function, level, geographic location, and scope. We evaluate compensation bi-annually, including performance and market-related factors.

Our salaries are benchmarked against market Total Cash Compensation for the geographic location of our job posting. Compensation for some roles is structured as On Target Earnings (OTE = base + commission/variable) while for others it is structured as Salary only.

To comply with local legislation and ensure transparency, we share salary ranges on all job postings. Skills, experience and other factors help determine the final salary we offer which may vary from the original range posted. 

Additionally, all permanent team members are eligible to participate in various benefits plans as part of their overall compensation package.

Salary Range: 

$ 145,000 -165,000 CAD

#LI-Hybrid 

The Strategic Enterprise Account Executive role is an outside sales position responsible for developing, managing, and closing business for Strategic Enterprise customers in the North America region and is an integral part of the field sales organization. This person will partner with our demand generation, solutions engineering, and product teams to guide prospective customers through a solutions sales journey of modernizing their cloud platform architecture.  This position will require you to develop a deep understanding of the specific challenges customers are facing to help them positively achieve their business outcomes with Upbound’s solutions. 

This role will work cross-functionally with product, marketing, sales development and customer success to provide a tight-knit customer relationship, account leadership and direction in both the pre-sales and post-sales processes.

In this role, you will:  

• Carry a sales quota that aligns with Upbound’s revenue goals.
• Function as the primary point of contact and the face of Upbound for new prospects and customers.
• Conduct sales activities including prospecting and developing opportunities within existing customer accounts.
• Manage complex strategic enterprise sales motions with multiple prospect engagement points.
• Ensure the successful rollout and adoption of Upbound products and services in partnership with pre-and-post sales engineering and support.
• Take ownership of your business by documenting the buying criteria, process, and owners to ensure pipeline accuracy.
• Look for and implement improvements to sales processes, tools, and materials.
• Travel to customer sites and industry conferences and events as needed.

You are a good fit if you have:

• Proven track record of consistently meeting or exceeding assigned annual/quarterly goals and targets and consistently ranked top 1-2 on your team.
• Sold to large enterprise G2K companies and adept at navigating global, multi-national organizations.
• Sold AI, Cloud, or Infrastructure platform oriented products.
• Experience in solution and value selling in the enterprise cloud, cloud-native, and AI product spaces
• Correctly estimate qualifying opportunities based on MEDDICC.
• Drive to build a business, hunger to find and close deals, and pride in the growth of the business.
• Relentless focus on customer success and meeting the needs of present and future customers.
• Experience building positive professional relationships with senior IT and business executives.
• Clear and articulate written, verbal, online, and in-person communication skills.
• Professionalism, polish, attention to detail, and strong follow-up.
• A collaborative mindset and willingness to help solve problems outside of your immediate lane.
• Fun in your job and enjoy what you do.

It’s a plus if you: 

• Strong understanding of cloud-native infrastructure, AI solutions, and/or Infrastructure as Code tooling (Terraform, Ansible, Chef).
• Significant experience selling disruptive technology into focused markets.

 #LI-REMOTE

Who we are:

MasterClass is the streaming platform where the world’s best come together so anyone, anywhere, can access and be inspired by their knowledge and stories. We put you in the room with the creators, thinkers, makers and leaders who have changed the world, so that you can change yours.

Members get unprecedented access to 200+ instructors and classes across a wide variety of fields, including Arts & Entertainment, Business, Design & Style, Sports & Gaming, Writing and more. Step into Nas’ recording studio and Gordon Ramsay’s kitchen, and go behind the big screen with James Cameron. Design your career with Elaine Welteroth, get ready to win with Lewis Hamilton, perfect your pitch with Shonda Rhimes and discover your inner negotiator with Chris Voss.

We’re a remote-first workforce with collaborative work spaces in San Francisco and Kitchener, Ontario, and employees in several U.S. states. If you’re interested in joining a dynamic, culture-driving company—where learning invaluable
skills is all in a day’s work—we invite you to apply.

Snapshot of the Role:

We’re looking for a Staff Infrastructure  Engineer who operates as a technical leader and force multiplier across the platform. This is a senior individual contributor role for someone who designs systems that scale beyond a single team, sets technical direction, and elevates how infrastructure is built and operated across MasterClass.

You’ll lead and provide direction for  cloud infrastructure, developer platforms, video infrastructure, and emerging AI/ML infrastructure—partnering closely with product engineering, content production, data, and AI teams. This role is ideal for someone who combines deep systems expertise with strong software engineering, thrives in ambiguity, and takes ownership from strategy through execution.

This is not a people-management role, but it carries significant technical leadership responsibility.

What You Will Do:

• Set technical direction for core infrastructure systems, balancing reliability, scalability, security, and developer velocity.
• Design and lead implementation of complex, cross-team infrastructure initiatives (AWS, EKS, CI/CD, shared platforms).
• Build production-grade software to power infrastructure automation, tooling, and internal platforms.
• Drive org-wide improvements in observability, incident response, reliability engineering, and cost efficiency.
• Lead video infrastructure initiatives  to evolve video delivery and CDN strategies for global scale and performance.
• Partner with AI and Data teams to define and build GPU-powered infrastructure, model-serving platforms, and GenAI inference/training workflows.
• Act as a technical mentor and reviewer, raising the bar for infrastructure design and operational excellence across teams.
• Lead by example during incidents, postmortems, and critical architectural decisions.

About You (Requirements):

• 10+ years building and operating cloud-native production systems.
• Strong expertise in:
  • AWS architecture and large-scale cloud operations
  • Kubernetes / EKS (networking, RBAC, Helm, autoscaling, cluster-level debugging)
  • Infrastructure as Code (Terraform preferred)
  • CI/CD and automation (GitHub Actions, Argo, or similar)
• Proven ability to design and build infrastructure software, not just operate systems.
• Deep understanding of distributed systems, networking, Linux internals, and cloud security.
• A track record of driving step-function improvements in reliability, scalability, or developer experience.
• Strong written and verbal communication skills; able to influence technical decisions across teams.

Who You Are

• You think in systems and leverage, not just tasks.
• You care deeply about craftsmanship, clarity, and long-term maintainability.
• You enjoy solving ambiguous, cross-functional technical problems.
• You’re pragmatic—you optimize for impact over novelty.
• You raise the bar through mentorship, design reviews, and thoughtful collaboration.
• You’re energized by both strategic architecture and hands-on implementation.

Nice To Haves

• AI/ML infrastructure, GPU scheduling, or distributed training
• Model serving frameworks (e.g., Triton, vLLM, TensorRT-LLM)
• Infrastructure autoscaling strategies, including application workloads, databases, and GenAI workloads
• KEDA, Karpenter, service mesh, or multi-cluster architectures
• HLS/DASH packaging or video encoding pipelines
  
  

  Nice-to-haves are not required; each represents a direction in which our infrastructure is evolving.

At MasterClass, we believe we put our best work forward when our employees bring together ideas that are diverse in thought. We are proud to be an equal opportunity workplace and are committed to equal employment opportunity regardless of race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or any other characteristic protected by applicable federal, state or local law. In addition, MasterClass will provide reasonable accommodations for qualified individuals with disabilities.  If you have a disability or special need, we would like to know how we can better accommodate you.