Who we are

About Stripe

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

About the team

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

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

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

What you’ll do

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

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

Responsibilities

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

Who you are

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

Minimum requirements

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

Preferred qualifications

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

Who we are

About Stripe

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

About the team

The Stripe Assistant team is transforming how users interact with Stripe by building an intelligent and proactive assistant that not only answers users’ queries but efficiently resolves issues and provides valuable business insights. We leverage LLMs and agentic systems to elevate the user experience across Stripe—from the dashboard to support surfaces—and we enable other teams to build and integrate their AI agents on our platform. We’re evolving from a helpful support tool to a trusted pilot that anticipates, optimizes, and executes on behalf of our users.

What you’ll do

As a Senior Machine Learning Engineer on the Stripe Assistant team, you’ll own the end-to-end ML and agent architecture that makes Stripe Assistant safe, reliable, and deeply useful. You’ll set the strategy for how the Assistant executes high-trust actions, delivers accurate analytical answers across Stripe and the broader web, orchestrates capabilities across many tools and agents, and grounds responses in authoritative Stripe and user data—so users can resolve issues quickly and confidently.

You’ll drive conversation continuity and personalization across surfaces, evolve the Assistant into a proactive partner that anticipates user needs, and deepen its presence in the dashboard to streamline critical workflows. You’ll establish rigorous evaluation and SLOs and deliver step‑change improvements in quality, latency, cost, and availability—paving the way for configurable levels of autonomy and, ultimately, a dependable operating layer over a merchant’s Stripe account.

Responsibilities

Our team operates fluidly and here are some problems you may tackle:

• Establish trustworthy, human-in-the-loop execution for high-trust “write” actions—prioritizing user control, transparency, accountability, and auditability so customers can delegate with confidence.
• Define and evolve the Assistant’s capability and governance model across hundreds of tools and agents, balancing power, permissions, and consistency at scale.
• Raise answer quality and usefulness by grounding in authoritative Stripe knowledge and live user data, building cross-surface memory and personalization, and making the Assistant proactive and present in the dashboard.
• Explore and apply optimal machine learning methods to improve Stripe Assistant’s overall performance, including but not limited to fine-tuning LLMs with RLHF, synthetic data generation, optimizing RAG pipelines via domain‑specific embedding and retriever fine‑tuning, and automatic prompt tuning, etc.
• Make quality and reliability a product: set and meet SLOs, build rigorous evaluation and benchmarking loops, and drive sustained improvements in latency, cost, and availability.
• Lead as a tech lead: mentor and grow engineers, uphold high bars for code quality, security, observability, and operational rigor, and align cross‑functionally to ship safely and fast.

Who you are

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

Minimum requirements

• 5+ years in AI/ML and backend engineering.
• Applied LLM experience: RAG/embeddings, tool use/function calling, agentic planning/orchestration, fine-tuning, code generation, evaluations, etc.
• Proficient in Python (Ruby is a plus); strong distributed systems fundamentals.
• Experience working closely with product management, design, other engineers, and other cross-functional partners.

Preferred qualifications

• Experience operating ML systems at global scale with stringent SLOs—balancing reliability, latency, and cost—with privacy, security, and compliance by design.
• Experience building products where AI/ML is core; as well as balancing short-term product priorities with long-term AI/ML improvements.
• Track record building ML platforms, especially those that enable multiple teams to collaborate together.
• Strong technical leadership and communication: mentoring and elevating engineers, elevating AI/ML awareness and posture within organizations, setting architectural direction, and driving alignment in ambiguity.

Join us to build a trustworthy, proactive AI operating layer for every Stripe merchant—advancing safety, reliability, and insight at global scale. If you’re ready to help take Stripe Assistant from copilot to full autopilot and shape how businesses connect with Stripe, we’d love to hear from you.

About the Role

The Cloud Inference team scales and optimizes Claude to serve the massive audiences of developers and enterprise companies across AWS, GCP, Azure, and future cloud service providers (CSPs). We own the end-to-end product of Claude on each cloud platform, from API integration and intelligent request routing to inference execution, capacity management, and day-to-day operations.

Within Cloud Inference, the model & inference launch team owns the validation pipeline for our inference server and load balancer on these platforms. We're responsible for every inference change — model launches, performance improvements, safeguard integrations — landing on cloud platforms with correctness, performance, and reliability intact.

This is high-leverage infrastructure work: validation has to be fast and cheap enough to run on the same accelerators that serve customers, trustworthy enough to replace manual checks, and consistent enough that a change working on Anthropic first-party means it works everywhere. This directly determines how fast frontier models and features ship to every cloud platform, and how quickly performance wins reach production — reclaiming capacity at a time when compute is our scarcest resource.

What You'll Do

• Be on the critical path for frontier model launches, bringing up inference for new model architectures and shipping them to cloud platforms in lockstep with our first-party platform
• Work with the core inference team to bring new inference features (e.g. structured sampling, prompt caching, and more) to cloud platforms, owning the platform-specific integration that gets them to production
• Identify and dive deep on the gaps that make inference behave differently across first-party and CSPs — config drift, observability, deployment patterns, hard cross-platform bugs — and fix them at the source rather than building platform-specific workarounds
• Design, build, and own the CI/CD infrastructure for the inference server and load balancer across cloud platforms, with shadow traffic, performance baselines (throughput and latency), and correctness checks that catch regressions before production
• Drive down merge-to-production cycle time by making validation faster, more parallel, and cost-effective enough to run on the same constrained accelerator pool that serves customers, without trading away reliability 
• Analyze observability data across providers to identify performance bottlenecks, cost anomalies, and regressions, and drive remediation based on real-world production workloads

You May Be a Good Fit If You:

• Have a strong interest in LLM serving; prior inference or ML experience is not required 
• Have significant software engineering experience, with a strong background in high-performance, large-scale distributed systems serving millions of users
• Have a track record of building automation or test infrastructure that measurably improved release velocity or reliability
• Have experience building or operating services on at least one major cloud platform (AWS, GCP, or Azure), with exposure to Kubernetes, Infrastructure as Code, or container orchestration
• Thrive in cross-functional collaboration with both internal teams and external partners
• Are a fast learner who can quickly ramp up on new technologies, hardware platforms, and provider ecosystems
• Are highly autonomous and take ownership of problems end-to-end, including work that falls outside your job description

Strong Candidates May Also Have Experience With:

• LLM inference optimization, batching, and caching strategies
• Capacity-constrained scheduling or shared-resource test infrastructure
• Solid understanding of multi-region deployments, request routing, load balancing, global traffic management
• Working with CSP partner teams to scale infrastructure across multiple platforms, navigating differences in networking, security, privacy, and managed service
• Proficiency in Python or Rust

Join Airtable as a Product Security Engineer and play a pivotal role in shaping the security of our rapidly evolving platform as we expand our AI and LLM-powered offerings. You will join the team responsible for safeguarding the application layer of Airtable’s platform.

You will partner closely with product engineering teams to build paved roads, frameworks, and automated controls that make the secure path the easy path for our engineering teams. You will help influence application security at scale, ensuring our products are secure by design.

What you'll do

• Develop self-service security frameworks and "paved roads" that allow engineering teams to ship secure code by default.
• Focus on automated guardrails for common vulnerabilities, while prioritizing deep-dive design reviews into complex business logic and data isolation issues (for example, multi-tenant isolation and authorization/permission bypasses) that automated tools cannot catch.
• Partner with product and engineering teams to review designs early, contribute to threat modeling for new features and complex initiatives, and provide clear, actionable security guidance.
• Research emerging threats and evolving best practices, specifically regarding AI and LLM safety, and implement controls to secure these workflows.
• Manage and evolve our approach to external penetration testing and bug bounties, driving remediation for findings and treating vulnerability management as an engineering problem.
• Contribute to the long-term roadmaps, metrics, and strategic planning for the security team.
• (Senior/Staff L5+) Lead complex threat modeling sessions for major product launches and define secure coding standards, and actively mentor other engineers to raise the technical security bar across the organization.

Who you are

• 4+ years of experience in product security or application security, with experience shipping production code. Please note this is not an early career position.
• You have a strong background in computer science or a related field, with proficiency in writing clean, maintainable code.
• You have deep familiarity with JavaScript or TypeScript, Node.js, and modern web application frameworks, and can reason about the security implications of systems built on them.
• You have hands-on experience securing LLM integrations and identifying prompt injection or data leakage risks.
• You are proficient in writing and reviewing code and treat security as an engineering problem to be solved with software, not just policies.
• You excel at communicating complex security risks to non-security stakeholders and enjoy collaborating cross-functionally to find solutions that balance security with engineering velocity.
• You are comfortable working in a fast-paced environment, navigating ambiguity, continuously learning about emerging threats and technologies, and contributing to long-term security strategy.

Airtable is an equal opportunity employer. We embrace diversity and strive to create a workplace where everyone has an equal opportunity to thrive. We welcome people of different backgrounds, experiences, abilities, and perspectives. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status or any characteristic protected by applicable federal and state laws, regulations and ordinances. Learn more about your EEO rights as an applicant. 

VEVRAA-Federal Contractor

If you have a medical condition, disability, or religious belief/practice which inhibits your ability to participate in any part of the application or interview process, please complete our Accommodations Request Form and let us know how we may assist you. Airtable is committed to participating in the interactive process and providing reasonable accommodations to qualified applicants.

#LI-remote

Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities.

About the General Agents Team

The General Agents team, part of Scale’s Enterprise organization, builds robust general agents for customer use cases and applications. The team sits at the intersection of frontier agent development and real-world deployment, translating state-of-the-art reasoning and agentic capabilities into reliable, production-grade systems that drive real economic value. Our agents are scalable systems built around recurring enterprise problem domains, with a strong emphasis on generalization, extensibility, and deployment across many customers.

About the Role

As a Senior/Staff Machine Learning Engineer (MLE) on the General Agents team, you’ll play a critical role in designing, building, and deploying production-ready AI agents that solve high-impact enterprise problems. You will work across the full agent lifecycle—from model and system design to evaluation, deployment, and iteration—bridging cutting-edge agentic techniques with the constraints and requirements of real customer environments.

You will:

• Design and implement end-to-end agent systems that combine LLM reasoning, tool use, memory, and control logic to solve recurring enterprise use cases.
• Build scalable, reliable agent architectures that can be deployed across many customers with varying data, tools, and constraints.
• Develop evaluation frameworks, datasets, environments, and metrics to measure agent performance, reliability, and business impact in production settings.
• Collaborate closely with product managers, customers, data annotators, and other engineering teams to translate enterprise requirements into robust agent designs.
• Productionize frontier agent techniques (e.g., planning, multi-step reasoning and tool-use, multi-agent patterns) into maintainable, observable systems.
• Own deployment, monitoring, and iteration of agent systems, including failure analysis and continuous improvement based on real-world usage.
• Contribute to technical direction and architectural decisions for general agent development best practices and methods, with increasing scope and leadership at the Staff level.

Ideally you’d have:

• 5+ years of experience building and deploying machine learning or AI systems for real-world, production use cases.
• Strong engineering fundamentals, supported by a Bachelor’s and/or Master’s degree in Computer Science, Machine Learning, AI, or equivalent practical experience.
• Deep understanding of modern LLMs, prompt-, context-, and system-level optimization, and agentic system design.
• Proven proficiency in Python, including writing production-quality, testable, and maintainable code.
• Experience building systems that integrate models with external tools, APIs, databases, and services.
• Ability to operate in ambiguous problem spaces, balancing research-driven approaches with pragmatic product constraints.
• Strong communication skills and comfort working in customer-facing or cross-functional environments.

Nice-to-haves:

• Hands-on experience building AI agents using modern generative AI stacks (OpenAI APIs, commercial or open-source LLMs).
• Experience with agent frameworks, orchestration layers, or workflow systems (e.g., tool calling, planners, multi-agent setups).
• Familiarity with evaluation, monitoring, and observability for LLM-powered systems in production.
• Experience deploying ML systems in cloud environments and operating them at scale.
• Experience fine-tuning or adapting foundation models using methods like supervised fine-tuning (SFT), reinforcement learning with verifiable rewards (RLVR), and low-rank adaptation (LoRA) to improve agent performance on domain-specific tasks.
• Interest in shaping the future of general-purpose enterprise agents and their real-world impact.

About the Role

We’re looking for a Senior Engineer to help build the next-generation inference platform that supports embedding models used for semantic search, retrieval, and AI-native experiences in MongoDB Atlas.

You’ll join the broader Search and AI Platform organization and collaborate with ML researchers and engineers from our Voyage.ai acquisition. Together, we’re building infrastructure for real-time, low-latency, and high-scale inference — fully integrated with Atlas and designed for developer-first experiences.

As a Senior Engineer, you'll focus on building core systems and services that power model inference at scale. You'll own key components of the infrastructure, work across teams to ensure tight integration with Atlas, and contribute to a platform designed for reliability, performance, and ease of use.

We're looking to speak with candidates in Palo Alto for our hybrid working model.

What You’ll Do

• Design and build components of a multi-tenant inference platform integrated directly with MongoDB Atlas, supporting semantic search and hybrid retrieval
• Collaborate with AI engineers and researchers to productionize inference for embedding models and rerankers — enabling both batch and real-time use cases
• Contribute to platform capabilities such as latency-aware routing, model versioning, health monitoring, and observability
• Improve performance, autoscaling, GPU utilization, and resource efficiency in a cloud-native environment
• Work across product, infrastructure, and ML teams to ensure the inference platform meets the scale, reliability, and latency demands of Atlas users
• Gain hands-on experience with tools like vLLM and container orchestration with Kubernetes

Who You Are

• 5+ years of experience building backend or infrastructure systems at scale
• Strong software engineering skills in languages such as Go, Rust, Python, or C++, with an emphasis on performance and reliability
• Experienced in cloud-native architectures, distributed systems, and multi-tenant service design
• Familiar with concepts in ML model serving and inference runtimes, even if not directly deploying models
• Knowledge of vector search systems (e.g., Faiss, HNSW, ScaNN) is a plus
• Comfortable working across functional teams, including ML researchers, backend engineers, and platform teams
• Motivated to work on systems integrated into MongoDB Atlas and used by thousands of developers

Nice to Have

• Experience integrating infrastructure with production ML workloads
• Understanding of hybrid retrieval, prompt-driven systems, or retrieval-augmented generation (RAG)
• Contributions to open-source infrastructure for ML serving or search

Why Join Us

• Be part of building the AI foundation of the world’s most popular developer data platform
• Collaborate with ML researchers from Voyage.ai to bring novel ideas into scalable systems
• Tackle challenging problems in inference, observability, and distributed infrastructure
• Work in a culture that emphasizes mentorship, ownership, and technical excellence

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, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type and makes all hiring decisions without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Req ID: 4263317053

About the role

Why this role is exciting

Why you'll love it here:

• 💰 Competitive Compensation. For this role our salary is targeted at $105-$140k USD per year. Final offer amounts are determined by factors such as experience and expertise. We take a geo neutral approach to compensation within the US, meaning that we pay based on job function and level, not location. 
• 🏆  Syndio Equity. So you can share in Syndio’s success.
• 🏝  Flexible Vacation Policy. We encourage our team to recharge when they need to, plus paid sick & safe time, compassion leave, parental leave, and voting leave. 
• 🩺  Medical, Dental, Vision. Syndio pays 90% of employee premiums, and 50% for dependents.
• 🏥  Life Insurance & Disability. Syndio covers the full premium.
• 🏦 401(k). To help you save for your future
• 📍 Remote-first in the following approved U.S. states: AZ, CA, CO, CT, DC, FL, GA, ID, IL, IA, MD, MA, MN, NE, NJ, NY, OH, OR, PA, RI, SC, SD, TX, UT, VT, VA, WA, and WI #LI-Remote

Role Progression:

In the 1st Month:

• Complete onboarding on the Syndio platform and the "Decision Intelligence" vision.
• Master the new Integration Platform and current data loading artifacts.
• Shadow 2-3 strategic client implementations and identify potential automation opportunities.
• Contribute to a pilot migration of an existing client’s data into the new platform.

At 3 Months:

• Independently lead technical implementations for new clients.
• Execute data migrations for a segment of the existing client base into the new Integration platform.
• Build reusable "Implementation Artifacts" (scripts, prompts, templates) that reduce time-to-value for the whole team.
• Contribute to the design of our new Platform’s Implementation process, identifying automation and other artifacts to minimize the client’s time to value.

By 6 Months:

• Manage a portfolio of high-complexity implementations for Syndio’s most strategic accounts utilizing automation and other artifacts to maximize client’s value in minimum time.
• Help achieve the goal of migrating 70% of the client base to the new Integration platform solution.
• Serve as a subject matter expert for "Process Embedding," ensuring clients are fully adopting the platform’s advanced setup features.

The interview overview

Below you'll find an outline of the interview plan for our Forward Deployed Engineer position. Please note that this is what we expect the process to look like; we may ask you for supplemental information or require an additional step before making a final decision.

1. 30 min phone call with a member of our Talent Team.
2. 45-60 min Zoom deep dive with the Hiring Manager (Director of Forward Deployed Engineering).
3. 75 min hands-on technical interview with a Senior Engineer.
4. 2-3 video interviews with key members of the Customer Success and Product teams.
5. 30 min interview with the SVP of Engineering - Data Strategy.

What we do  

You’ll join a software engineering team building internal AI solutions that support teams across The Trade Desk. We leverage large language models, retrieval‑augmented generation (RAG), agentic systems, and enterprise platforms like Microsoft Copilot and Anthropic Claude to improve productivity, streamline workflows, and reduce operational friction.

Our team also plays a key role in AI enablement across the company—supporting teams as they adopt Copilot, Claude and similar tools, designing and deploying custom AI agents, and guiding partners through their AI journey from idea to impact.

As a Senior AI Engineer on this team, you’ll be an end-to-end owner—collaborating closely with stakeholders, identifying opportunities, and delivering tools that make a real impact. We’re a nimble, fast-paced, and highly collaborative group that thrives on transforming the way teams operate and driving greater value across The Trade Desk.

What you’ll do: 

Some of the work that you will be doing to help us deliver on our mission is:

• Design and deploy intelligent agentic systems that integrate large language models (LLMs) with enterprise data, tools, and workflows using frameworks like LangChain, LlamaIndex, and Semantic Kernel.
• Develop Retrieval-Augmented Generation (RAG) applications using tools like Azure AI Search, vector databases, and secure enterprise connectors to deliver contextual insights.
• Build and deploy agents using Microsoft Copilot, Copilot Studio, Anthropic Claude, and similar platforms to help teams operationalize solutions within enterprise guardrails.
• Build and iterate on conversational agents that solve real-world problems, meet stakeholder needs, and deliver measurable business value.
• Deliver high-impact features by collaborating across teams, leading through ambiguity, and aligning technical solutions with business goals.
• Drive quality and performance through automated testing, monitoring, and data-driven evaluation of success criteria, user adoption, and operational efficiency.
• Mentor teammates and contribute to a culture of innovation, technical excellence, and continuous learning.

Who you are: 

• You have a Bachelor’s/Master’s level degree in computer science or relevant engineering-related field or equivalent experience.
• You have 8-10+ years of software engineering experience, including 1-2+ years working on AI-powered systems or products.
• You are proficient in Python and comfortable with additional languages such as C#, SQL, or TypeScript/React.
• You’re excited about AI enablement, including helping teams adopt platforms like Microsoft Copilot, Anthropic Claude and Copilot Studio, building agents, and guiding others through their AI journey.
• You have a good foundational knowledge of or hands-on experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel) and prompt engineering using LLM APIs.
• You have experience productionizing applications and implementing CI/CD pipelines to ensure reliable, scalable deployments.
• You are skilled in data ingestion and transformation using APIs, ETL pipelines, and connectors, and familiar with vector databases and retrieval strategies.
• You communicate clearly across technical and non-technical audiences and thrive in a collaborative, cross-functional environment.
• You are a fast learner who adapts quickly to new technologies and solves complex problems with creativity and pragmatism.

#LI-TP1

A variety of technical opportunities is one of the best things about working at The Trade Desk as a software engineer, which is why we do not expect you to know every technology we use when you start. What we care about is that you can learn quickly and find solutions to complex problems using the optimum tools for the job. What you know is less important than how well you learn and innovate. We are not seeking engineers who know all the answers; we need engineers who can invent answers no one has thought of yet and find answers to the questions yet to be asked. 

The Trade Desk does not accept unsolicited resumes from search firm recruiters. Fees will not be paid in the event a candidate submitted by a recruiter without an agreement in place is hired; such resumes will be deemed the sole property of The Trade Desk. The Trade Desk is an equal opportunity employer. All aspects of employment will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.

[LA JOBS ONLY] The Trade Desk will consider qualified applicants with criminal histories for employment in a manner consistent with the requirements of the Los Angeles Fair Chance Initiative for Hiring, Ordinance No. 184652.

[SF JOBS ONLY] Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

#LI-TP1

About the Team

As a Senior+ Agentic Analytics Engineer at Opendoor, you will join the Data organization and help build something that doesn't exist at most companies: an Agentic Analytics team. This is a high-impact IC role at the intersection of data science, data engineering, and AI.

Opendoor has adopted a "Default to AI" philosophy—if AI can handle it, AI should handle it. We're not theorizing about AI transformation; we're shipping it.

Why This Role

Most analytics teams are stuck in reactive mode—fielding ad-hoc requests and building dashboards that go stale. We're building something different: AI systems that proactively tell leaders what they should focus on, why it matters, and what to do about it.

If you want to define what analytics looks like in an AI-first company, this is it.

What You'll Do

Build Proactive Intelligence Systems

• Design and deploy AI agents that monitor business performance and surface actionable insights without being asked

• Architect systems that shift analytics from "answering questions" to "anticipating needs"

• Create intelligent alerting that distinguishes signal from noise and recommends specific actions

Create AI-Powered Analytics Tools

• Develop natural language interfaces that let business leaders query data conversationally

• Build semantic layers that translate business concepts into data structures optimized for LLM reasoning

• Ship internal tools that transform how Opendoor makes decisions at every level

Own the Analytics-to-Action Pipeline

• Design data models that support automated analysis, pattern detection, and AI agent interactions

• Build workflows that connect insight generation to recommended actions

• Establish feedback loops that make our AI systems smarter over time

Drive Leverage Across the Business

• Identify high-value opportunities where AI can augment human decision-making

• Implement end-to-end solutions using Claude, custom agents, and modern AI tooling

• Measure impact rigorously—we care about decisions influenced, not dashboards built

We're Looking for Teammates Who Have

Technical Foundation

• 5+ years of experience in analytics, data science, or data engineering, with increasing scope and ownership

• Expert-level SQL with demonstrated ability to design complex data models and optimize for both human and AI consumption

• Strong Python proficiency for data engineering, automation, and AI agent development

• Experience with modern data warehouses (Snowflake, BigQuery, or similar) and the broader data stack (dbt, Airflow, etc.)

AI & Automation Expertise

• Hands-on experience building and deploying AI agents or LLM-powered applications in production

• Deep understanding of LLM capabilities, limitations, and prompt engineering best practices

• Experience architecting semantic layers or natural language interfaces for data access

• Proven ability to identify high-ROI automation opportunities and ship end-to-end solutions

Analytics & Business Acumen

• Track record of driving measurable business impact through analytics—not just producing analyses, but influencing decisions

• Strong analytical intuition—you know what questions matter before they're asked

• Experience translating ambiguous, cross-functional business problems into technical solutions

• History of operating autonomously and setting direction, not just executing on defined projects

Leadership & Influence

• Experience mentoring other analysts or engineers, formally or informally

• Demonstrated ability to influence senior stakeholders and drive alignment across teams

• Comfort operating in ambiguity and shaping strategy, not just responding to it

• Track record of building systems and processes that scale beyond yourself

Builder Mindset

• You ship products, not just dashboards 

• You'd rather build something useful in a week than something perfect in a quarter

• You measure success by business impact, not technical complexity

• You're energized by creating leverage—building once so others benefit forever

Bonus Points If You Have

• Experience in real estate, fintech, or marketplace businesses

• Background in marketing analytics, sales operations, product analytics, or pricing/economics

• History of building tools or platforms that replaced recurring analyst work

• Experience leading technical projects or small teams

About the Team

As a Senior+ Agentic Analytics Engineer at Opendoor, you will join the Data organization and help build something that doesn't exist at most companies: an Agentic Analytics team. This is a high-impact IC role at the intersection of data science, data engineering, and AI.

Opendoor has adopted a "Default to AI" philosophy—if AI can handle it, AI should handle it. We're not theorizing about AI transformation; we're shipping it.

Why This Role

Most analytics teams are stuck in reactive mode—fielding ad-hoc requests and building dashboards that go stale. We're building something different: AI systems that proactively tell leaders what they should focus on, why it matters, and what to do about it.

If you want to define what analytics looks like in an AI-first company, this is it.

What You'll Do

Build Proactive Intelligence Systems

• Design and deploy AI agents that monitor business performance and surface actionable insights without being asked

• Architect systems that shift analytics from "answering questions" to "anticipating needs"

• Create intelligent alerting that distinguishes signal from noise and recommends specific actions

Create AI-Powered Analytics Tools

• Develop natural language interfaces that let business leaders query data conversationally

• Build semantic layers that translate business concepts into data structures optimized for LLM reasoning

• Ship internal tools that transform how Opendoor makes decisions at every level

Own the Analytics-to-Action Pipeline

• Design data models that support automated analysis, pattern detection, and AI agent interactions

• Build workflows that connect insight generation to recommended actions

• Establish feedback loops that make our AI systems smarter over time

Drive Leverage Across the Business

• Identify high-value opportunities where AI can augment human decision-making

• Implement end-to-end solutions using Claude, custom agents, and modern AI tooling

• Measure impact rigorously—we care about decisions influenced, not dashboards built

We're Looking for Teammates Who Have

Technical Foundation

• 5+ years of experience in analytics, data science, or data engineering, with increasing scope and ownership

• Expert-level SQL with demonstrated ability to design complex data models and optimize for both human and AI consumption

• Strong Python proficiency for data engineering, automation, and AI agent development

• Experience with modern data warehouses (Snowflake, BigQuery, or similar) and the broader data stack (dbt, Airflow, etc.)

AI & Automation Expertise

• Hands-on experience building and deploying AI agents or LLM-powered applications in production

• Deep understanding of LLM capabilities, limitations, and prompt engineering best practices

• Experience architecting semantic layers or natural language interfaces for data access

• Proven ability to identify high-ROI automation opportunities and ship end-to-end solutions

Analytics & Business Acumen

• Track record of driving measurable business impact through analytics—not just producing analyses, but influencing decisions

• Strong analytical intuition—you know what questions matter before they're asked

• Experience translating ambiguous, cross-functional business problems into technical solutions

• History of operating autonomously and setting direction, not just executing on defined projects

Leadership & Influence

• Experience mentoring other analysts or engineers, formally or informally

• Demonstrated ability to influence senior stakeholders and drive alignment across teams

• Comfort operating in ambiguity and shaping strategy, not just responding to it

• Track record of building systems and processes that scale beyond yourself

Builder Mindset

• You ship products, not just dashboards 

• You'd rather build something useful in a week than something perfect in a quarter

• You measure success by business impact, not technical complexity

• You're energized by creating leverage—building once so others benefit forever

Bonus Points If You Have

• Experience in real estate, fintech, or marketplace businesses

• Background in marketing analytics, sales operations, product analytics, or pricing/economics

• History of building tools or platforms that replaced recurring analyst work

• Experience leading technical projects or small teams

ABOUT THE TEAM:

The Developer Platform team builds the tools and infrastructure that power software development at Anduril. We own the company's primary developer CLI (2,300+ engineers, 93k+ invocations), CI/CD pipelines serving 3,500+ engineers across 23 product lines in the US, Australia, and UK, deployment and release management systems, and Anduril's LLM adoption platform. We are standing up a new agentic development initiative to build the next generation of AI-powered developer infrastructure. The team is growing fast and this is a ground-floor opportunity to define what agentic software development looks like at a company building mission-critical defense systems.

WHAT YOU'LL DO:

• Build multi-agent orchestration infrastructure that moves AI coding agents from individual developer machines to servers executing work autonomously across repositories at company scale
• Design and implement an agent-optimized, real-time knowledge base that gives AI agents deep context on codebases, architecture, and operational patterns
• Build a skills and plugin platform that lets any team encode their domain knowledge into reusable AI capabilities
• Improve CI/CD reliability and developer experience across 23 product lines
• Create release tooling that simplifies shipping software to production environments and robotic platforms
• Operate and evolve Anduril's LLM adoption platform: model rollouts, capacity management, cost attribution, and developer onboarding

REQUIRED QUALIFICATIONS:

• Strong software engineering fundamentals in one or more of: Go, Python, TypeScript
• An entrepreneur, builder, PM, and designer rolled into one. We need people with outstanding software taste who can identify the right problem, design the solution, build it, and ship it in days, not quarters.
• A passion for developer tooling. You notice friction in your own workflow and cannot help but fix it. You spend 4 hours sharpening the axe and 30 minutes chopping wood.
• Demonstrated ability to quickly learn and adapt to unfamiliar technologies across multiple domains
• Must be a U.S. Person due to required access to U.S. export controlled information or facilities

PREFERRED QUALIFICATIONS:

• Experience building developer tools, CLIs, CI/CD systems, or platform infrastructure
• Experience with Kubernetes, Nix, or cloud infrastructure (AWS/Azure)
• Genuine interest in LLMs and agentic systems as applied to developer productivity. If you are already building with AI coding agents in your daily workflow, you will feel right at home.
• Prior work on LLM integrations, prompt engineering, or agent frameworks

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

With over half a billion rides and counting, Lyft is solving hard problems at scale, leveraging AI and Machine Learning to better serve our customers. The Artificial Intelligence, Machine Learning, and Operations Research Platforms team (AIMLOR) is seeking a Senior Machine Learning Engineer to focus on building AI Platform components enabling critical AI applications across Lyft. Expertise with GenAI and platform building is a core requirement for this role. In this role, you will contribute to our platform which supports real-time, online, and offline AI and ML model execution, development, and iteration. You will work with a team of highly motivated Machine Learning and Software Engineers on challenging problems, defining solutions to directly impact systems across the entire business.

If you are interested in building an AI Platform at scale, with applications across each facet of the company, we are searching for you.

If you are a creative and critical thinker with experience in AI and machine learning systems, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you.

Responsibilities:

• Contribute to the roadmap and architecture based on technology and business needs
• Write well-crafted, well-tested, readable, maintainable code
• Have a good grasp and ability to explain the various tradeoffs made in decisions
• Participate in code reviews to ensure code quality and distribute knowledge 
• Build features from tech specification to positive execution
• Incorporate considerations for business context and failure modes in your work
• Proactively participate in resolving ongoing incidents 
• Unblock, support, effectively communicate, and obtain buy-in within your team to achieve results
• Share your knowledge by giving brown bags and tech talks

Experience:

• BSc/MSc in Computer Engineering, Computer Science, Machine Learning related field or relevant work experience
• 5+ years of ML engineering experience working in any of these stacks: Python, GO, Java, etc.
• Experience with ML serving/training/deployment infrastructure; familiarity with cloud providers (e.g. AWS, Azure, Google Cloud); familiarity with GenAI ecosystem: LLMs, prompt engineering, MCP, RAG; hands-on experience with LLM fine-tuning techniques and frameworks (e.g. PEFT, LoRA); knowledge on deploying self-hosted LLMs (e.g. Llama, Mistral) for specialized tasks
• Experience with GenAI/LLM infrastructure, agent frameworks (e.g. LangChain, LangGraph); MLOps tooling (MLflow, Airflow)
• Preferred: Experience with AI assisted coding such as Cursor or Claude Code

Benefits:

• Great medical, dental, and vision insurance options with additional programs available when enrolled
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• 401(k) plan with company match to help save for your future
• In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Subsidized commuter benefits
• Monthly Lyft credits and complimentary Lyft Pink membership

Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the Seattle area is $149,780 - $187,220, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

With over half a billion rides and counting, Lyft is solving hard problems at scale, leveraging AI and Machine Learning to better serve our customers. The Artificial Intelligence, Machine Learning, and Operations Research Platforms team (AIMLOR) is seeking a Senior Machine Learning Engineer to focus on building AI Platform components enabling critical AI applications across Lyft. Expertise with GenAI and platform building is a core requirement for this role. In this role, you will contribute to our platform which supports real-time, online, and offline AI and ML model execution, development, and iteration. You will work with a team of highly motivated Machine Learning and Software Engineers on challenging problems, defining solutions to directly impact systems across the entire business.

If you are interested in building an AI Platform at scale, with applications across each facet of the company, we are searching for you.

If you are a creative and critical thinker with experience in AI and machine learning systems, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you.

Responsibilities:

• Contribute to the roadmap and architecture based on technology and business needs
• Write well-crafted, well-tested, readable, maintainable code
• Have a good grasp and ability to explain the various tradeoffs made in decisions
• Participate in code reviews to ensure code quality and distribute knowledge 
• Build features from tech specification to positive execution
• Incorporate considerations for business context and failure modes in your work
• Proactively participate in resolving ongoing incidents 
• Unblock, support, effectively communicate, and obtain buy-in within your team to achieve results
• Share your knowledge by giving brown bags and tech talks

Experience:

• BSc/MSc in Computer Engineering, Computer Science, Machine Learning related field or relevant work experience
• 5+ years of ML engineering experience working in any of these stacks: Python, GO, Java, etc.
• Experience with ML serving/training/deployment infrastructure; familiarity with cloud providers (e.g. AWS, Azure, Google Cloud); familiarity with GenAI ecosystem: LLMs, prompt engineering, MCP, RAG; hands-on experience with LLM fine-tuning techniques and frameworks (e.g. PEFT, LoRA); knowledge on deploying self-hosted LLMs (e.g. Llama, Mistral) for specialized tasks
• Experience with GenAI/LLM infrastructure, agent frameworks (e.g. LangChain, LangGraph); MLOps tooling (MLflow, Airflow)
• Preferred: Experience with AI assisted coding such as Cursor or Claude Code

Benefits:

• Great medical, dental, and vision insurance options with additional programs available when enrolled
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• 401(k) plan with company match to help save for your future
• In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Subsidized commuter benefits
• Monthly Lyft credits and complimentary Lyft Pink membership

Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the San Francisco area is $162,800 - $203,500, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

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.

You may be a good fit if you:

• Have significant software engineering experience, particularly with distributed systems
• Are results-oriented, with a bias towards flexibility and impact
• Pick up slack, even if it goes outside your job description
• Enjoy pair programming (we love to pair!)
• Want to learn more about machine learning systems and infrastructure
• Thrive in environments where technical excellence directly drives both business results and research breakthroughs
• Care about the societal impacts of your work

Strong candidates may also have experience with:

• High-performance, large-scale distributed systems
• Implementing and deploying machine learning systems at scale
• Load balancing, request routing, or traffic management systems
• LLM inference optimization, batching, and caching strategies
• Kubernetes and cloud infrastructure (AWS, GCP, Azure)
• Python or Rust

Representative projects:

• Designing intelligent routing algorithms that optimize request distribution across thousands of accelerators
• Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads
• Building production-grade deployment pipelines for releasing new models to millions of users
• Integrating new AI accelerator platforms to maintain our hardware-agnostic competitive advantage
• Contributing to new inference features (e.g., structured sampling, prompt caching)
• Supporting inference for new model architectures
• Analyzing observability data to tune performance based on real-world production workloads
• Managing multi-region deployments and geographic routing for global customers

Deadline to apply: None. Applications will be reviewed on a rolling basis. 

Deadline to apply: None. Applications will be reviewed on a rolling basis. 

Who we are

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort, and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn’t coming; it’s here, and we need builders, innovators, and problem solvers to help us create it.

Who you are

Metropolis is seeking a Senior AI Engineer to join our Applied AI organization, a team purpose-built to rebuild how the company operates from an AI-first perspective. You will be the builder at the heart of this transformation, designing and shipping AI-powered tools and automation pipelines that replace manual, repetitive work across finance, operations, revenue, and beyond. This is a hands-on engineering role with enormous scope: you will own systems end-to-end, from the LLM prompt layer through to production deployment, working side-by-side with Process Analysts who understand the business deeply. If you want to see your work directly change how a company functions — not someday, but now — this is the role.

What you'll do

• Design, build, and ship AI-powered automation tools and internal applications that transform manual business processes into AI-first workflows
• Architect and maintain LLM-based systems, including prompt pipelines, agentic workflows, tool-calling integrations, and retrieval-augmented generation (RAG) setups
• Build and maintain data pipelines that connect source systems (Snowflake, internal APIs, SaaS tools) to AI workflows, ensuring data quality and reliability
• Partner with Process Analysts to understand how business functions work today, translate requirements into engineering specifications, and iterate based on real user feedback
• Own production reliability for the systems you build — monitoring, alerting, and iterating on AI outputs to maintain quality over time
• Evaluate and integrate emerging AI tooling (models, frameworks, APIs) to ensure Metropolis is always leveraging the best available capabilities
• Contribute to internal standards for AI development: prompt management, evaluation frameworks, model selection, and system architecture

What we're looking for

• 6+ years of software engineering experience, with 2+ years of hands-on experience designing, building, and deploying LLM-based or AI-powered applications in production
• Strong Python skills — you write clean, maintainable code and are comfortable building APIs, data pipelines, and backend services
• Practical experience with LLM APIs (OpenAI, Anthropic, or similar), prompt engineering, and agentic patterns (function calling, multi-step reasoning, tool use)
• Familiarity with data engineering fundamentals: SQL, data transformation, working with cloud data warehouses (Snowflake preferred)
• Experience with workflow orchestration tools (e.g., Airflow, Prefect, or similar) and cloud infrastructure (AWS preferred)
• A strong instinct for product quality — you care about whether the tools you build are actually useful, not just technically functional
• Ability to work autonomously in a fast-moving environment, manage competing priorities, and ship iteratively rather than waiting for perfection

While not required, these are a plus:

• Experience with vector databases, embeddings, or semantic search is a plus

Our Stack

• Languages + Frameworks: TypeScript, React, Scala (principally), Java (limited)
• Datastores: MySQL, PostgreSQL, Snowflake
• Cloud: AWS
• Version control: Git & GitHub
• AI Tooling: Copilot on GitHub and Claude Code
• Observability: Datadog

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection

When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $170,000.00 USD to $200,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis' total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans, and more. #LI-CM1 #LI-Onsite

ABOUT BEZOS ACADEMY

At Bezos Academy, we believe all children deserve the great start that excellent early education provides, including in under-resourced communities. Our mission is to nurture the potential in every child to become a creative leader, original thinker, and lifelong learner by inventing the solutions needed to scale early childhood education. We are a unique organization that realizes our mission in two ways. First, we operate a multi-state network of schools in under-resourced communities, offering quality Montessori-inspired preschool at no cost to families. Second, we create tools, products, technology, and other solutions designed to reach young children and their caregivers well beyond the walls of our schools. We aspire to have a profound, large-scale impact on children ages zero to five. At Bezos Academy, we are committed to expanding access to play-focused preschool education in underserved communities, aiming to improve long-term educational, social, and developmental outcomes in ways that create meaningful and lasting impact.

ABOUT THE ROLE

As a Senior AI Applications Engineer at Bezos Academy, you will help build AI-powered software applications that support teachers’ abilities to deliver measurable results in early childhood education. As a hands-on, results-driven software developer, you will play a pivotal role in developing intelligent systems for teachers, staff and families with a small product development team. Your products will both thrill and delight their users and enable our national school network to nurture young children’s originality, foster self-agency, cultivate a love for learning, and spark joy.

You have a proven track record of combining machine-learning models, high-quality data, and human-centered workflows into production-ready tools; you consistently deliver solutions that solve human problems. Resourceful throughout the software-development lifecycle—from research and prototyping to deployment, monitoring, and evaluation—you work effectively despite constraints on time and resources. In past roles, you have successfully launched AI-powered applications in collaboration with product-development teams. As a software engineer with a customer mindset, you take pride in applying practical AI workflows and sound software-engineering principles to build high-impact AI products. Adept at working from scratch, you navigate ambiguity, iterate quickly, and shape solutions that earn customer love. Hands-on experience with evaluations, inference validation, and AI guardrails has helped you strengthen the safety, performance, and ethics of AI features. You recognize exceptional work when you see it and instill that same passion in others.

In this role, you will focus on building, measuring, and iterating for children. Motivated equally by great products and great impact, you are deeply inspired by our mission to expand access to quality early childhood education and experiences.

LOCATION

• Washington, Arizona, Florida, Kentucky, or Texas, within two hours’ drive to multiple Bezos Academy preschools (please see our website for-school locations); Seattle, WA preferred.
• Relocation support is available for those willing to relocate to Seattle, WA

COMPENSATION AND BENEFITS

• This is a full-time, benefits-eligible, salaried position.
• The full salary range for this position, across applicable United States geographies, is $157,000 - $298,000 per year. The upper portion of the salary range is typically reserved for employees who have been in the role for multiple years and have demonstrated strong performance over time. Starting salary will vary by location, qualifications, and prior experience.
• This role includes 15 paid days of vacation, 4 days of paid personal time off, 9 paid days of sick (care) time, 9 paid holidays, 5 paid days off for an organization-wide winter break, and additional time off if required by applicable law. Benefits for this role include medical, dental, and vision insurance, life insurance, disability insurance, a 401(k) plan with a 4% employer contribution match, paid parental leave, an employer-matched flexible spending account for dependent care, and more. Please see here for details.

MINIMUM QUALIFICATIONS

• Bachelor’s degree or equivalent experience
• Eight or more years of experience developing and deploying full-stack applications, including two or more years working on AI-powered applications in production environments
• Proficiency in Python for backend development and integrating AI capabilities
• Working knowledge of TypeScript and SQL for full-stack development and data handling
• Experience integrating pre-trained foundation models, including large language models (LLMs) and multi-modal models, into production applications
• Familiarity with model evaluation techniques, such as prompt testing, output validation, and performance monitoring
• Experience with AWS services, especially those relevant to AI applications (e.g., Bedrock, Lambda, EC2, S3, RDS, DynamoDB)
• Understanding of AI safety practices, including inference validation, implementing guardrails, and handling personally identifiable information (PII) and sensitive data responsibly
• Ability to speak, read, and write English fluently
  

PREFERRED QUALIFICATIONS

• Experience with LangChain or similar frameworks for orchestrating LLM workflows and agentic behavior (e.g., tool use, planning, memory)
• Familiarity with AWS AgentCore
• Exposure to vector databases and embedding techniques, especially in retrieval-augmented generation (RAG) workflows
• Experience implementing AWS Bedrock Guardrails or similar safety mechanisms
• Understanding of LLM evaluation strategies, including prompt engineering and human feedback loops
• Experience with DevOps practices, including CI/CD pipelines, test automation, and infrastructure-as-code tools (e.g., AWS CDK)

Please click here for a full job description. 

Bezos Academy participates in E-Verify and will provide the federal government with employee Form I-9 Information to confirm authorization to work in the U.S. Bezos Academy only uses E-Verify once a candidate has accepted a job offer and completed the Form I-9. If E-Verify cannot confirm that an employee is authorized to work, Bezos Academy will give the employee written instructions and an opportunity to contact the Department of Homeland Security (DHS) or Social Security Administration (SSA) so the employee can begin to resolve the issue before any adverse employment action is taken. For more information about your right to work, please see the Notice of Right to Work.

Persons in these roles are expected to work from our offices in Seattle. On-site requirements vary based on position and team. If you have questions about on-site work arrangements for this role, please ask your recruiter.

Our base salary range is $126,000 - $189,000, and in addition we have generous bonus plans to provide a competitive compensation package. 

Who You Are:

You are a seasoned full-stack engineer who thrives in greenfield environments where you have broad scope and the  opportunity to wear multiple hats. You excel in building impactful, AI-powered solutions and take pride in delivering intuitive, high-performance user experiences. In this role, you'll work closely with UX designers, AI/ML experts, and research scientists, both internally and at partner institutions, to create seamless interfaces that empower users to  interact effectively with our AI systems. You're energized by the opportunity to collaborate directly with researchers  to translate their needs into production applications that advance real scientific discovery.

Who We Are: 

The Agentic Applications team builds open, production-grade AI systems that power scientific discovery. We focus on developing intelligent agents that help researchers explore literature, synthesize knowledge, and accelerate their work across real-world scientific use cases. The team combines strong engineering practices with close collaboration across Ai2's product and research orgs to deliver tools used by millions of researchers and developers worldwide.

Your Next Challenge:

The essential functions include, but are not limited to the following:

• Work closely with UX designers, product managers, and research scientists to develop rich UI experiences using React and robust backend services in Python
• Engage in the entire software development lifecycle, from ideation and design to implementation and testing to deployment and operational support, with a strong sense of ownership for results
• Scale our systems in a cost-effective and sustainable manner and be a driving force behind continuous improvements in reliability and automation
• Improve team velocity through contributions to software design, feature development, platform and framework enhancements, capacity planning, and deployment tooling
• Help set and maintain best practices in how we measure, monitor, and respond to system availability, latency, and general application health
• Communicate effectively across engineering, product, and research teams to align priorities and drive projects to completion
• Mentor less-senior engineers on the team in both technical and non-technical skills

What You’ll Need:

• Bachelor's degree and 8+ years of technical experience; relevant experience may substitute for education
• Professional experience with web development using JavaScript, HTML, and CSS
• Strong Python engineering skills
• Proficiency with front-end frameworks such as React
• Experience with AWS, Google Cloud, or similar cloud platforms
• Experience with analytics and observability tools like Heap, Datadog, or similar for monitoring performance, system health, and user interactions
• Solid understanding of integrating AI-powered capabilities into applications, including prompt engineering, memory management, agent workflows, and external tool integrations
• Strong communication skills and a sense of ownership for results

Physical Demands and Work Environment:

The physical demands described here are representative of those that must be met by a team member to successfully perform the essential functions of this position. Reasonable accommodations may be made to enable individuals with disabilities to perform the functions.

• Must be able to remain in a stationary position for long periods of time. 
• The ability to communicate information and ideas so others will understand. Must be able to exchange accurate information in these situations. 
• The ability to observe details at close range.
• Can work under deadlines.

A Little More About Ai2:

Ai2 is a Seattle based non-profit AI research institute founded in 2014 by the late Paul Allen. Our mission is building breakthrough AI to solve the world’s biggest problems. We develop foundational AI research and innovation to deliver real-world impact through large-scale open models, data, robotics, conservation, and beyond.

In addition to Ai2’s core mission, we also aim to contribute to humanity through our treatment of each member of the Ai2 Team. Some highlights are:

• We are a learning organization – because everything Ai2 does is ground-breaking, we are learning every day. Similarly, through weekly Ai2 Academy lectures, a wide variety of world-class AI experts as guest speakers, and our commitment to your personal on-going education, Ai2 is a place where you will have opportunities to continue learning alongside your coworkers. 
• We value diversity - We seek to hire, support, and promote people from all genders, ethnicities, and all levels of experience regardless of age. We particularly encourage applications from women, non-binary individuals, people of color, members of the LGBTQA+ community, and people with disabilities of any kind. 
• We value inclusion - We understand the value that people's individual experiences and perspectives can bring to an organization, and we are building a culture in which all voices are heard, respected and considered.
• We emphasize a healthy work/life balance – we believe our team members are happiest and most productive when their work/life balance is optimized. While we value powerful research results which drive our mission forward, we also value dinner with family, weekend time, and vacation time. We offer generous paid vacation and sick leave as well as family leave.
• We are collaborative and transparent – we consider ourselves a team, all moving with a common purpose. We are quick to cheer our successes, and even quicker to share and jointly problem solve our failures.
• We are in Seattle – and our office is on the water! We have mountains, we have lakes, we have four seasons, we bike to work, we have a vibrant theater scene, and we have so much else. We even have kayaks for you to paddle right outside our front door. We welcome interest from applicants from outside of the United States.
• We are friendly– chances are you will like every one of the 200+ (and growing) people who work here. We do. 

Ai2 is proud to be an Equal Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. You may view the related Know Your Rights compliance poster and the Pay Transparency Nondiscrimination Provision by clicking on their corresponding links. 

This employer participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S. If E-Verify cannot confirm that you are authorized to work, this employer is required to give you written instructions and an opportunity to contact the Department of Homeland Security (DHS) or Social Security Administration (SSA) so you can begin to resolve the issue before the employer can take any action against you, including terminating your employment. Employers can only use E-Verify once you have accepted a job offer and completed the Form I-9.

We are committed to providing reasonable accommodations to employees and applicants with disabilities to the full extent required by the Americans with Disabilities Act (ADA). If you feel you need a reasonable accommodation pursuant to the ADA, you are encouraged to contact us at recruiting@allenai.org.

Benefits:  

• Team members and their families are covered by medical, dental, vision, and an employee assistance program.
• Team members are able to enroll in our health savings account plan, our healthcare reimbursement arrangement plan, and our health care and dependent care flexible spending account plans.
• Team members are able to enroll in our company’s 401k plan.
• Team members will receive $125 per month to assist with commuting or internet expenses and will also receive $200 per month for fitness and wellbeing expenses.
• Team members will also receive up to ten sick days per year, up to seven personal days per year, up to 20 vacation days per year and twelve paid holidays throughout the calendar year.
• Team members will be able to receive annual bonuses and can participate in the long-term incentive plan.

Note: This job description in no way states or implies that these are the only duties to be performed by the team members(s) of this position. Team members will be required to follow any other job-related instructions and to perform any other job-related duties requested by any person authorized to give instructions or assignments. All duties and responsibilities are essential functions and requirements and are subject to possible modification to reasonably accommodate individuals with disabilities. To perform this job successfully, the team member(s) will possess the skills, aptitudes, and abilities to perform each duty proficiently. Some requirements may exclude individuals who pose a direct threat or significant risk to the health or safety of themselves or others. The requirements listed in this document are the minimum levels of knowledge, skills, or abilities. This document does not create an employment contract, implied or otherwise, other than an at will relationship.

What We're Looking For

We are looking for a Senior Application Security Engineer to help secure our AI, machine learning, and inference platforms. This is a hands on technical role focused on building security into modern AI infrastructure, inference systems, and developer platforms.

You will work closely with platform engineers, ML engineers, and infrastructure teams to identify risks, design secure architectures, and build security tooling that enables engineers to move quickly and safely.

This role is execution focused. You will drive technical implementation, perform deep security reviews, and help build out our application security capabilities alongside the CISO and engineering leadership.

This role can be based out of one of our office hubs (San Francisco or Seattle) with in-office requirements of at least 2 days per week, plus occasional team/company offsites. We are not able to offer visa sponsorship for this position at this time.

What You’ll Do

Secure AI and Machine Learning Systems

• Perform threat modeling across AI platforms, inference services, and ML pipelines
• Identify risks such as prompt injection, model extraction, adversarial inputs, and data leakage
• Review model serving architectures and inference pipelines
• Partner with ML engineers to secure training, fine tuning, and deployment workflows
• Help design isolation and security controls for multi tenant AI workloads

Application Security Engineering

• Perform architecture and design security reviews
• Conduct targeted code reviews for high risk components
• Identify security gaps in APIs, micro-services, and distributed systems
• Build secure patterns for authentication, authorization, and service to service communication
• Help engineering teams implement secure defaults and guardrails

Inference Platform Security

• Secure customer facing inference APIs and services
• Protect against abuse, model extraction, and adversarial behavior
• Design rate limiting, isolation, and workload protection controls
• Build monitoring and detection for anomalous inference behavior

AI Supply Chain and Model Security

• Evaluate open source models and dependencies
• Secure model artifacts and distribution pipelines
• Implement integrity validation and provenance controls
• Help secure container images and runtime environments

Security Automation and Tooling

• Build security automation for AI and application pipelines
• Integrate security scanning into CI/CD workflows
• Develop tooling to help engineers detect and fix issues early
• Improve developer experience with security guardrails

What You'll Need

Required Experience

• Strong background in application security engineering
• Experience performing threat modeling and architecture reviews
• Experience securing APIs and distributed systems
• Experience working in cloud environments such as AWS, GCP, or Azure
• Experience with containers and Kubernetes
• Strong scripting or programming skills such as Python, Go, or similar
• Experience working closely with engineering teams to implement security improvements

AI and Machine Learning Experience

• Experience securing ML pipelines, inference systems, or data platforms
• Familiarity with risks such as prompt injection, model extraction, and adversarial inputs
• Experience reviewing model serving architectures
• Understanding of training data security and data leakage risks

It's a Strong Plus If You Have

• Red team or offensive security experience
• Experience crafting payloads and evaluating CVEs for exploitability in diverse environments
• Experience with GPU infrastructure or high performance computing
• Experience with Hugging Face, PyTorch, TensorFlow, or similar frameworks
• Experience with LLM systems, RAG pipelines, or agent frameworks
• Experience building security automation pipelines
• Experience securing multi tenant infrastructure

What Success Looks Like

• Security is embedded into AI platform architecture early
• Engineering teams ship quickly with secure defaults
• Inference platforms are resilient against abuse and extraction
• Model pipelines are secure and auditable
• Security tooling scales with engineering growth

Why This Role Matters

This role sits at the intersection of application security, AI infrastructure, and developer platforms. You will help define how we secure modern AI systems while enabling engineers to move quickly and safely.

You will work closely with engineering leadership and the CISO to build practical, scalable security capabilities that support rapid innovation in AI and machine learning.

Compensation

The role

We are seeking a Staff Software Engineer, AI to join the Member Growth organization with the mission of bringing the value of AI to SoFi Members. This role will be pivotal in supporting our members’ financial journeys through advanced personalization and AI-driven solutions, and lead the development of internal frameworks, tools, and applications that bring cutting-edge capabilities to our marketing, communications, and measurement systems.

Our goal is to help members navigate their path to financial independence by providing the specific tools, resources, and guidance they need to succeed. We aim to be a trusted partner in their financial lives, delivering timely, tailored insights that build long-term confidence. Achieving this requires a thoughtful, highly personalized approach to every user’s unique financial needs.

The ideal candidate possesses a deep understanding of Artificial Intelligence (AI) and Machine Learning (ML) systems, paired with a passion for building next-generation products. At SoFi, we pride ourselves on the seamless collaboration between Product, Design, and Engineering; as such, you will be involved in the entire product lifecycle—from initial ideation to deployment and iterative evolution. We are committed to a philosophy of continuous learning, and we expect you to be equally dedicated to your own professional growth and the mentorship of your fellow team members.

What you’ll do

• Drive technical architecture, design decisions and cross-functional discussions for AI and ML-based solutions

• Deliver highly available and scalable services in a production environment

• Lead the design, development and testing of systems

• Lead code and system design reviews

• Help translate product requirements into user stories and technical solutions

• Mentor other engineers, support the technical culture, and help grow the team

• Generate ideas for new initiatives and technologies

• Communicate with product managers, data scientists, data engineers, and other software developers

• Consistently demonstrate extremely high levels of technical knowledge, ingenuity, and creativity

• Develop and apply advanced technologies, engineering principles, theories, and concepts

• Take initiative and produce timely results in a fast-paced and sometimes ambiguous environment

What you’ll need

• Bachelor’s Degree in Computer Science or related field, or equivalent experience

• 8+ years programming experience on a modern stack with expertise in Python 

• Experience working with new technologies in the AI stack, such as building Agents, creating MCP servers, fine tuning models, prompt engineering, and performance evaluation

• Experience working with applications that leverage Large Language Models (LLMs), such as integrating LLMs, designing prompts, or exploring their practical applications

• Our core stack is Java/ Kotlin/ Spring/ AWS/ Snowflake, and we run on Kubernetes in a cloud-native service oriented architecture. You should be comfortable developing using some or all of these technologies

• You should have worked on a SOA or microservice-based application

• Strong sense of ownership; driving a project from inception to completion

• Pragmatic approach towards handling tech debt versus shipping new features

• Experience working in a collaborative coding environment, refining designs together, working through code reviews and managing pull requests

We're building a new capability at Pinterest: embedding AI-native engineering directly inside our business functions. The AI Solutions Engineer will partner with teams across Marketing, Finance, Sales, HR, Legal, and other functions to surface high-value automation opportunities, then design and ship the AI-powered tools that bring those opportunities to life.

This is a hands-on, mid-level software engineering role for someone who is equally comfortable reading a business process flowchart and writing production-grade Python. You'll work end-to-end — from discovery and scoping through prototyping, launch, and iteration — using the latest agentic frameworks, tool-calling patterns, and responsible AI practices.

What you'll do:

• Discover and scope AI opportunities: Partner with internal teams across corporate functions to understand their workflows, pain points, and goals, and identify high‑value AI/automation opportunities. Map and improve business processes: document current workflows, identify bottlenecks, and propose AI‑enabled changes that deliver clear business outcomes (e.g., time or cost savings, improved quality or compliance).
• Design end-to-end AI solutions: Design and implement AI‑enabled tools and workflows that integrate with existing systems and data sources, and that are intuitive for non‑technical users.
• Build and ship production-quality software: Write clean, maintainable code and tests. Use standard CI/CD and environment practices. Implement logging, monitoring, and basic guardrails so we can understand and improve performance, quality, cost, and reliability over time.
• Pilot, rollout, and drive adoption: Pilot, roll out, and drive adoption of solutions by working closely with end‑users, gathering feedback, and iterating based on real‑world usage.
• Champion for responsible AI: Ensure solutions follow privacy, security, and compliance expectations, especially when working with sensitive or regulated data.
• Build for reuse: Create and share reusable patterns, components, and documentation to make future AI/automation work faster and more consistent across teams.
• Accelerate Workflows with Generative AI and Automation: Leverage AI to accelerate execution (e.g., draft, prototype, outline), explore alternative solutions using AI (iterate, compare approaches), synthesize information with AI (summarize, distill key themes), automate repeatable work (documentation, reporting, QA checks)

What we're looking for:

We're looking for mid-level engineers who have already shipped something real with AI — and who can work as a peer with non-technical business partners, not just as an order-taker. Specifically, you bring:

• Software engineering foundation. A CS, Engineering, Data Science, or related degree (or equivalent experience), with demonstrated ability to build and operate production systems — backend services, internal tools, integrations, or data applications.
• Hands-on AI and automation delivery. You've shipped AI-powered or automation-driven solutions in a real environment. Examples include: a multi-step workflow automation, an internal tool using document understanding or intelligent routing, or an integration of an AI service (e.g., OpenAI, Anthropic, Vertex AI, Bedrock) into an existing system.
• Agentic AI literacy. You understand how modern agentic systems are constructed — the difference between local and remote agents, how MCP (Model Context Protocol) works, what Agent Skills and Hooks are for, and how A2A (Agent-to-Agent) coordination is structured. You can reason about when to use these patterns and when simpler approaches suffice.
• System design and architecture thinking. You can sketch a data flow, reason about integration points, evaluate trade-offs between approaches, and design for failure — including fallbacks, retry logic, timeouts, and human escalation paths.
• Data and security judgment. You understand data access controls, the risks of giving AI broad access to sensitive information, PII minimization, audit logging, and what responsible data handling looks like in an enterprise environment. You know to filter data before it reaches the model, not after.
• Business function acumen. You can engage credibly with stakeholders in Marketing, Finance, Sales, HR, Legal, or Operations — understanding their workflows, KPIs, and constraints well enough to scope solutions that fit their real needs.
• Clear, collaborative communication. You can explain architecture trade-offs to a Finance Manager and debug a prompt failure with an engineer in the same afternoon. You build trust by being direct about limitations, not by over-promising.
• Preferred Qualifications
  • Experience working embedded with or alongside corporate / G&A functions (Finance, Legal, HR, Marketing, Sales Operations, or similar).
  • Practical experience with agentic frameworks such as LangGraph, Claude Agent SDK, or comparable tooling
  • Familiarity with MCP server design — including building, deploying, and securing MCP-compliant tool servers.
  • Experience designing and evaluating AI outputs at scale: eval sets, sampling pipelines, human-in-the-loop review queues, or A/B testing of AI-powered features.
  • Exposure to responsible AI frameworks: data minimization, differential privacy concepts, model output auditing, or working in PII-sensitive / regulated domains.
  • Experience with RAG (Retrieval-Augmented Generation) pipelines, vector databases, or enterprise search integrations.
  • Familiarity with CI/CD for AI: prompt versioning, model version pinning, regression testing for LLM-powered features.
  • Bachelor’s/Master’s degree in a relevant field such as Computer Science or equivalent experience.
  • Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs.
  • Strong track record of critical evaluation and verification of AI-assisted work (e.g., testing, source-checking, data validation, peer review).
  • High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables.

Relocation Statement:

• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
  
  

In-Office Requirement Statement:

•  This role will need to be in the office for in-person collaboration 1-2 times every 6-months and therefore can be situated anywhere in the country.
  
  

#LI-REMOTE

#LI-KBF

Job Summary

The Director of Forward Deployed Engineering is the executive leader responsible for building and scaling the platform that accelerates Customer Experience Automation (CXA) and Agentic AI deployments across Talkdesk's largest enterprise customers. Rather than solving each customer engagement from scratch, you will lead a high-caliber team of engineers who create the reusable libraries, evaluation systems, and safe deployment infrastructure that make every subsequent implementation faster, more accurate, and increasingly differentiated.

This role requires a unique blend of strategic organizational leadership, deep technical expertise in AI/ML, and a platform-engineering mindset. Your work will feed critical field insights back to the core Product and Engineering teams and directly influence the long-term platform roadmap.

Duties and Responsibilities

• Platform Strategy & Vision: Define and execute the strategy for the FDE platform — a proprietary system of industry-verticalized prompt libraries, integration skills, and automated evaluation suites that accelerate CXA implementations and compound in value over time.

• Operational Excellence: Develop and execute the FDE operational strategy, defining the "golden path" for deployments, ensuring scalability, security, and high performance across all client environments.

• Cross-Functional Bridge: Serve as the primary liaison between Sales, Product Management, and Core Engineering. Advocate for platform capabilities that solve recurring customer pain points and align the field team with the product roadmap.

• Technical Governance: Identify and mitigate complex technical risks across agentic deployments. Ensure the team maintains technical excellence and follows best practices for RAG systems, multi-agent orchestration, API integrations, and secure data architecture.

• Team Development & Mentorship: Hire, manage, and mentor a team of FDEs. Foster a culture of platform thinking, high-stakes problem solving, and continuous learning in the rapidly evolving AI landscape.

• Executive Technical Authority: Act as the ultimate technical escalation point for customers. Build high-trust relationships with customer CTOs and VPs of Engineering during the most critical phases of the deployment lifecycle.
  
  

Qualifications

• Education: Bachelor’s or Master’s degree in Computer Science, AI/ML, or a related technical field.
• Experience: Minimum of 9–12 years of experience in software engineering or professional services, including at least 5 years in a significant leadership role (Manager or above) managing customer-facing technical teams.
• AI/ML Domain Expertise: Deep understanding of Agentic AI Architecture, including multi-agent orchestration, prompt engineering, and RAG (Retrieval-Augmented Generation).
• Technical Depth: Strong architectural knowledge of systems integration (APIs, webhooks, message queues) and the ability to review production-grade code in Python, Javascript, or Typescript.
• Field Experience: Proven track record of delivering high-stakes technical projects in complex enterprise environments (e.g., Healthcare, Financial Services, or CCaaS).
• Leadership Skills: Exceptional ability to motivate and grow a team of high-performing, autonomous "hybrid" engineers who excel at both coding and client interaction.
• Strategic Thinking: Demonstrated success in turning one-off customer solutions into scalable, repeatable engineering patterns.
• Communication: Mastery in translating "deep tech" AI concepts into business value for executive stakeholders.

Pay Range (Base Pay):   $260,000 - $409,000

Other Types of Pay: Based on level and role the employee may be eligible for long term incentives in the form of equity and short term incentives of either bonus or commission. 

Health Insurance: Medical, Dental, Vision, Life and Disability Insurance, Employee Assistance Program (EAP).

Retirement Benefits: 401(k) plan

Paid Time Off: Talkdesk offers an uncapped paid time off program for exempt employees and an accrual-based program for non-exempt employees; both are subject to manager approval and consistent with business needs.

Paid Holidays: Talkdesk offers 14 paid holidays each year. 

Paid Sick Leave: Exempt employees have uncapped paid time off and non-exempt sick leave follows accrual standards; both are subject to manager approval and consistent with business needs.

Method of Application: Apply online.

Application Window: The application window is expected to close at least 7 days from the posting date. The application was posted on 04/07/2026.

Benefits and perks listed above may vary based on the nature of your employment with Talkdesk.

All questions or concerns about this posting should be directed to the Talent team at Talent@talkdesk.com.

Security Engineer (Pentesting, Incident Response & Investigations)

Our Engineering teams follow a micro-service architecture approach to build the next generation of Talkdesk, with autonomous vertical teams owning their services end to end. We promote agile and collaborative practices, value peer reviews, and believe that true authority comes from knowledge, not position. Respect, curiosity, and continuous learning are core to how we work.

Are you passionate about breaking things to make them safer?

As a Security Engineer focused on Pentesting, Incident Response, and Security Investigations, you will play a key role in detecting, investigating, and preventing security incidents while proactively identifying weaknesses across our platforms and applications.

What you’ll do

Depending on your profile and experience, your responsibilities may include:

• Perform manual and automated penetration testing of web applications, APIs, cloud-based systems, and AI/ML models.

Conduct security assessments of AI-driven features, focusing on risks like prompt injection, data leakage, and adversarial attacks. Conduct security investigations to identify root causes, attack paths, and impact of security incidents.Lead or actively participate in incident response, including detection, containment, eradication, and post-incident reviews. Analyze logs, telemetry, and forensic artifacts to support investigations and threat hunting activities.

• Triage, validate, and prioritize findings from internal and external penetration tests.
• Work closely with engineering teams to explain vulnerabilities, recommend pragmatic remediations, and verify fixes.
• Support the development and improvement of incident response playbooks and processes.
• Perform threat modeling (e.g., STRIDE) to identify realistic attack scenarios.
• Continuously research emerging threats, attack techniques, and exploitation methods relevant to our environment, including the evolving AI threat landscape.
• Act as a security subject-matter expert (SME) during incidents and high-risk technical discussions.
• Help improve Talkdesk’s overall security posture through lessons learned and proactive testing.

Must have

Strong knowledge of application and systems security. Solid understanding of web technologies, networking, and common attack vectors. Practical experience with penetration testing tools and techniques

• Experience with the OWASP Top 10 for LLMs and common AI exploitation patterns

Experience conducting security investigations and incident responseUnderstanding of OWASP Top 10 and common exploitation patterns

• Knowledge of cryptographic concepts and their practical use (and misuse)
• Linux/Unix proficiency
• Experience analyzing logs and security events
• Scripting or coding experience in at least one general-purpose language (e.g., Python, Ruby, Java)
• Excellent written and verbal communication skills, with the ability to explain complex security issues clearly
• Fluent in English (written and spoken)
• Strong analytical and critical-thinking skills
• Comfortable working in fast-paced, sometimes high-pressure situations

Nice to have

• Experience testing cloud-native environments, especially AWS
• Familiarity with microservices architectures and API security
• Experience with web and mobile application security testing
• Exposure to DAST, SAST, or IAST tools (hands-on or triage-focused)
• Experience performing application architecture security reviews
• Familiarity with security standards and frameworks (e.g., ISO 27001, NIST, CIS, OWASP, SANS)
• Relevant certifications such as OSCP, OSWE, GSEC, GCIA, CISSP, or CISM
• Familiarity with technologies like Git, Ruby, Kotlin, RabbitMQ, Redis, MongoDB, or PostgreSQL

Pay Range (Base Pay):   $124,500 - $187,000

Other Types of Pay: Based on level and role the employee may be eligible for long term incentives in the form of equity and short term incentives of either bonus or commission. 

Health Insurance: Medical, Dental, Vision, Life and Disability Insurance, Employee Assistance Program (EAP).

Retirement Benefits: 401(k) plan

Paid Time Off: Talkdesk offers an uncapped paid time off program for exempt employees and an accrual-based program for non-exempt employees; both are subject to manager approval and consistent with business needs.

Paid Holidays: Talkdesk offers 14 paid holidays each year. 

Paid Sick Leave: Exempt employees have uncapped paid time off and non-exempt sick leave follows accrual standards; both are subject to manager approval and consistent with business needs.

Method of Application: Apply online.

Application Window: The application window is expected to close at least 7 days from the posting date. The application was posted on 04/29/2026.

Benefits and perks listed above may vary based on the nature of your employment with Talkdesk.

All questions or concerns about this posting should be directed to the Talent team at Talent@talkdesk.com.

About the role:

As a member of the Applied AI team at Anthropic, you will be a Forward Deployed Engineer (FDE) who embeds directly with our most strategic customers to drive transformational AI adoption. You will collaborate closely with customer teams to ship advanced AI applications that solve real world business problems. Our FDEs engage with customers to accelerate the adoption of existing products and create new applications built on our models.

Working closely with our Post-Sales, Product, and Engineering teams, you'll combine engineering expertise, an understanding of frontier AI applications, and customer-facing skills to understand customer workflows and develop innovative solutions that address complex business challenges while maintaining our high standards for safety and reliability.

You will sit at the frontier of enterprise AI deployments and serve as one of our founding FDEs who helps to shape our forward-deployed motion. We expect our FDEs to operate autonomously, thrive under ambiguity, and represent Anthropic at the highest level in customer environments. This is a significant responsibility: you’ll play a key role in championing our mission in the enterprise.

Responsibilities:

• Work within customer systems to build production applications with Claude models, ensuring that these products meet customer requirements.
• Deliver technical artifacts for customers like MCP servers, sub-agents, and agent skills that will be used in production workflows.
• Provide white glove deployment support for Anthropic products in enterprise environments.
• Identify and codify repeatable deployment patterns and contribute insights back to our Product and Engineering teams.
• Maintain strong knowledge of the latest developments in LLM capabilities, implementation patterns, and AI product development stacks.
• Build long term relationships with customers and proactively identify new opportunities for AI deployment throughout the lifecycle of an engagement.
• Potential Travel (based on location) to customer sites to build in person with customers. - Estimated 25% 
• Be a champion for Anthropic’s mission in the field.

You May Be a Good Fit If You Have:

• 3+ years of experience in a technical, customer facing role such as Forward Deployed Engineer, or as a Software Engineer with consulting experience. Former technical founders are also encouraged to apply.
• Production experience with LLMs including advanced prompt engineering, agent development, evaluation frameworks, and deployment at scale.
• Strong programming skills with proficiency in Python (and ideally in one or more additional languages like Typescript, Java, etc) and experience shipping production applications 
• High agency with an ability to navigate ambiguity present in complex organizations.
• High cooperation mindset for cross-organizational collaboration, balancing competing priorities with integrity.
• Passion for advancing safe, beneficial AI systems through creative technical applications.
• Strong communication skills to conduct discovery with customers and to convey technical concepts to diverse stakeholders while maintaining a low ego and collaborative approach.
• A background in financial services, healthcare/life sciences, or another enterprise vertical is a plus.
• Experience with enterprise IT systems and/or AI deployment patterns is a plus.
• Experience working as an FDE or in a professional services context is a plus.

About the role

As the Manager of the Partnerships Applied AI Solutions Architect team, you will drive adoption of frontier AI by enabling deployment of Anthropic’s products (Claude for Enterprise, Claude Code, API) through our Global and Regional System Integrators, cloud partners (AWS, GCP, Azure), and strategic technology partners.

You will build and lead a team of Partner Solutions Architects, establish processes and best practices for partner-led pre-sales engagements, and represent Anthropic as the technical lead on its most important partnerships. In collaboration with Sales, Partnerships, Product, and Engineering, you will help partners incorporate leading-edge AI into their practices, accelerate indirect revenue, and execute long-term GTM strategy while maintaining our best-in-class safety standards.

Responsibilities

• Team Leadership & Development: Hire, manage, and mentor a team of Partner Solutions Architects. Set goals, run reviews, and coach each team member toward high productivity and career growth.
• Strategic Technical Partnership: Act as the senior technical thought partner to Anthropic’s GTM partnerships team. Co-build partner strategy with aligned GTM leadership, drive key programs, and align cross-functional stakeholders (Sales, Product, Engineering) behind partner outcomes.
• Partner Enablement & Ecosystem: Embed your team with GSI and cloud partner technical teams to enable their AI practices, troubleshoot, and evangelize Anthropic in their developer communities. Represent Anthropic at partner events (GSI workshops, AWS/GCP summits, hackathons) and contribute technical content and thought leadership.
• Joint Solution Development: Lead partners in identifying high-value, industry-specific GenAI applications. Develop joint solutions and codify reference architectures and best practices to accelerate time to deployment.
• Customer Deal Support: Own the technical portion of partner-led pre-sales engagements. Intervene directly on strategic deals where partners are the primary delivery vehicle, providing deep solution architecture guidance.
• Product Feedback: Gather and validate feedback on Anthropic’s products from partner deployments and deliver it to Product and Engineering to inform roadmap and partner strategy.

You may be a good fit if you have

• 7+ years in technical customer-facing or partner-facing roles (Solutions Architect, Sales Engineer, Partner SE, TAM).
• 3+ years managing pre-sales or partner-facing technical teams; comfortable building foundational teams in ambiguous, fast-moving environments.
• Track record building and scaling partnerships with GSIs (e.g., Accenture, Deloitte, TCS, Infosys) and/or cloud providers (AWS, GCP, Azure).
• Deep understanding of partner-led selling and delivery: indirect revenue models, enablement at scale, and joint GTM motions.
• Technical depth in enterprise AI deployments: LLM architecture, prompt engineering, evaluation, API integrations, and production use cases.
• Exceptional communication and executive presence; able to build trusted relationships with C-suite, partner leadership, and engineering teams alike.
• A love of teaching and mentoring, and a passion for advancing safe, beneficial AI.

Strong candidates may also have

• 5+ years leading partner-facing SA teams through hypergrowth, including developing both senior and junior talent.
• Direct experience helping GSIs or consultancies build their AI/ML practice - enablement programs, certification paths, joint solution development.

About the role:

As a member of the Applied AI team at Anthropic, you will be a technical Product Engineer focused on becoming a trusted technical advisor to Digital Native Businesses - technology companies adopting the Claude API into their core products. You will work closely with customer product and engineering teams as they ship new products powered by Claude: advising on architecture design decisions, developing evaluation frameworks, and guiding customers through the most cutting-edge implementation patterns for LLMs.

Working closely with our Sales, Product, and Engineering teams, you'll guide a focused portfolio of customers from technical discovery through successful deployment. You'll combine deep engineering expertise with customer-facing skills to help customers unlock the full potential of Claude APIs and move their products closer to the frontier, while maintaining our high standards for safety and reliability.

Responsibilities:

• Serve as a specialist technical advisor to Anthropic customers as they deploy new products & workflows with our models: from discovery through deployment, coordinating internally across multiple teams to drive customer success
• Partner with account executives and solutions architects to translate customer business requirements into technical solutions
• Influence technical architecture decisions and customer product strategy by developing customized pilots, prototypes, and evaluation suites
• Lead hands-on technical workshops and code reviews with customer engineering teams
• Identify common design patterns and contribute insights back to our Product and Engineering teams
• Create scalable public and internal assets, documenting the latest LLM prompting, evaling, agentic, and architecture techniques
• Maintain strong knowledge of the latest developments in LLM capabilities, implementation patterns, and AI product development stacks
• Travel occasionally to customer sites for workshops, implementation support, and building relationships
• Attend conferences, lead speaking engagements, write blog posts and white papers on topics surrounding the AI space

You may be a good fit if you have:

• 4+ years of experience in technical roles such as Forward Deployed Engineer, Software Engineer or Technical Product Manager with a desire to work closely with customers. Former technical founders are also encouraged to apply.
• Production experience with LLMs including advanced prompt engineering, agent development and frameworks, evaluation frameworks, transcript analysis, MCP, and deployment at scale
• Strong programming skills with proficiency in Python or TypeScript and experience building production applications
• Ability to navigate ambiguity and execute across domains with intellectual openness, finding simple solutions to complex problems
• High cooperation mindset for cross-organizational collaboration, balancing competing priorities with integrity
• Passion for advancing safe, beneficial AI systems through creative technical applications
• Exceptional communication skills to convey technical concepts to diverse stakeholders while maintaining a low ego and collaborative approach

Please note this role requires 3 days in office per week. 

Deadline to apply: None. Applications will be reviewed on a rolling basis. 

We are seeking a talented and innovative Synthetic Data Engineer. In this role, you will design and implement domain-specific synthetic data generation pipelines, ensuring high-quality data management for training loops. Your expertise will drive the success of data processing and model training within the organization.

Responsibilities:

• Design domain-specific synthetic data generation (SDG) pipelines via self-instruct and constitutional prompting.
• Implement automated quality scoring and de-duplication systems.
• Manage data pipelines that feed directly into SFT and DPO training loops.

Qualifications:

• Proven experience building large-scale data pipelines (Airflow, Spark, Ray).
• Deep knowledge of prompt engineering for data generation.
• Familiarity with dataset distillation and bias mitigation.

Build AI that matters. We ship production GenAI apps for confidential federal programs across defense, national security, public safety, civilian, and military health where reliability, privacy, and safety aren’t optional. AFS is a technology company within global Accenture and a Glassdoor Top 100 Best Place to Work. You’ll join a collaborative, inclusive community with handson growth, certifications, and industry training. We ship in weeks, not quarters, and measure success with latency, reliability, safety, and cost. 

Confidentiality matters: We don’t disclose program details publicly. If you advance, we’ll share specifics during the process. 

Role Overview 

You’ll turn mission needs into secure, reliable, and scalable GenAI applications no model training required. This is a hands-on role across agentic workflows, RAG, prompt/policy design, LLM evaluation, and platform integration. You’ll own the end-to-end path from use case evaluation → production deployment → operational excellence, partnering with product, security, data, and SRE to ship features safely and at scale. 

What You’ll Do (Day to Day) 

• Design & ship mission grade GenAI: Build agentic workflows and RAG systems tailored to mission data and environments; target low hallucination, tight p95 latency, and predictable cost. 

• Agent frameworks & orchestration: Apply patterns from LangChain/LlamaIndex/Semantic Kernel; design task decomposition, tool use, guardrails, and recovery/fallback strategies. 

• Platform integration (no model training): Implement with AWS Bedrock, Azure OpenAI, Google Vertex AI, Amazon Kendra, and managed services (e.g., Document AI, Gemini, Gemma). 

• LLM selection & evaluation: Compare models for quality, safety, latency, cost; author/test prompts & policies; deploy with observability and safe rollback/fallback. 

• RAG done right: Build retrieval pipelines & vector search (Pinecone, Weaviate, OpenSearch, pgvector, FAISS/Chroma); handle data prep, chunking, metadata, and IRstyle evals (e.g., NDCG) to maximize signal to noise. 

• Production rigor: Instrument metrics/logs/traces; run A/B experiments; maintain incident playbooks; and implement safety & compliance guardrails. 

• SRE & FinOps for AI: Define SLIs/SLOs (quality/latency/safety/cost), run on call and postmortems, reduce MTTR; meter usage and optimize token/spend. 

• Reusable platform components: Ship SDKs, CI/CD templates, Terraform/IaC modules, evaluation harnesses that accelerate multiple mission team not one-off projects. 

• Operate in real world constraints: Deliver into hybrid, restricted, or air gapped environments with Zero Trust principles and audit ready controls. 

You'll Thrive Here If you have 

• End-to-end ownership of production systems: integration → deployment → observability → incident response. 

• Hands-on experience with LLMs, transformer based apps, and RAG in production. 

• Strong Python 

• Experience with vector search and retrieval (Pinecone, Weaviate, OpenSearch, pgvector, FAISS/Chroma) and grounding AI in enterprise/mission data. 

• U.S. Citizenship 

Nice to Have 

• Integration with leading cloud AI services or on prem inference stacks  

• Background in LLM evaluation, prompt authoring/testing, A/B experimentation, and LLM Ops. 

• Responsible AI expertise (privacy, security, bias, transparency, human in the loop) and data governance. 

• Experience implementing tool using agents for API integration and external data access. 

• Containerization & orchestration (Docker, Kubernetes, VMware) and scripting/automation (Linux Bash, PowerShell). 

• Prior work in regulated/secure environments (e.g., ATO, STIGs, Zero Trust) with fast shipping. 

• Familiarity with NVIDIA AI Foundations, OpenAI ChatGPT, and AI assisted dev tools (Cursor, Windsurf, Claude). 

• Contributions to internal frameworks or opensource; mentorship of engineers. 

• Clear communication with engineers, PMs, and security/compliance stakeholders. 

Who we are

Metropolis is an artificial intelligence company that uses computer vision technology to enable frictionless, checkout-free experiences in the real world. Today, we are reimagining parking to enable millions of consumers to just "drive in and drive out." We envision a future where people transact in the real world with a speed, ease, and convenience that is unparalleled, even online. Tomorrow, we will power checkout-free experiences anywhere you go to make the everyday experiences of living, working, and playing remarkable - giving us back our most valuable asset, time.

Who you are

Metropolis is seeking a Staff Software Engineer to join our Revenue Platform team. In this role, you will own the technical direction for our billing, payments, and invoicing infrastructure, charting the course for a system that already processes tens of millions in monthly transactions. You will balance immediate business needs with long-term architectural improvements, identifying high-impact enhancements and designing practical migration strategies to support our rapid growth.

As a technical leader, you will partner closely with engineering, finance, and operations teams to solve complex challenges involving pricing rules, subscription billing, and enterprise invoicing. You are a systems thinker who enjoys understanding how things work and building the roadmaps that improve a platform while it runs. Your work will directly shape how Metropolis monetizes its platform and expands into new verticals beyond parking, ensuring our financial systems remain resilient, compliant, and remarkably efficient.

What you’ll do

• Own the technical architecture and evolution of Metropolis's billing, payments, and invoicing systems, establishing standards for financial accuracy, transaction integrity, and compliance that ensure every dollar is correctly captured and accounted for
• Design and implement resilient payment processing with support for multiple payment gateways (Stripe,  etc.), intelligent routing between processors, retry strategies for failed transactions, and graceful handling of partial failures to maximize payment success rates
• Build comprehensive monitoring and reporting for revenue operations, including payment success rates, billing accuracy metrics, reconciliation dashboards, failed transaction alerts, and audit trails that provide visibility from customer transactions to accounting close
• Partner with finance and operations teams on payment failures, billing disputes, refund workflows, and reconciliation issues – building tools and automation that reduce manual intervention and improve mean time to resolution for customer-impacting revenue issues
• Drive adoption of revenue system best practices across services, including idempotent payment processing, distributed transaction handling, compensation workflows for failures, audit logging, and testing strategies that ensure financial correctness
• Own integrations with external systems, including payment gateways, ERP, data analytics, etc., ensuring reliable data flow and maintaining compliance requirements across the revenue stack

What we’re looking for

• 8+ years of hands-on engineering experience with a focus on building revenue systems like payment platforms
• Strong systems thinking for financial correctness with proven ability to design distributed revenue systems that handle edge cases gracefully: partial failures, duplicate requests, timing issues, currency conversion, tax calculation, and maintaining transaction integrity across service boundaries
• Database and financial data expertise, including transaction isolation, audit logging, point-in-time recovery, handling financial data migrations, and experience with systems that require both high availability and absolute correctness
• Payment gateway and integration experience with production knowledge of Stripe, PayPal, or similar processors; tax calculation services; accounting system integrations; and the operational reality of depending on external financial services, including compliance requirements like PCI-DSS
• Excellent technical communication with the ability to influence technical decisions across teams (particularly finance, accounting, and data teams), document complex systems, conduct post-mortems, and establish reliability standards organization-wide
• Experience with sophisticated usage of rapidly developing AI-assisted development skills in real-world codebases, including fluent use of Claude Code/GPT Codex/Windsurf or similar tools in multi-agent mode, spec-driven development (SDD),  MCP/skills optimization, context/prompt engineering
• Local to the Seattle area

While not required, these are a plus

• BS or MS in Computer Science or a relevant engineering discipline
• Expert-level revenue systems engineering with hands-on experience building billing platforms, payment processing pipelines, reconciliation systems, and handling challenges like idempotent transactions, failed payment retries, proration logic, multi-currency support, and revenue recognition – you've seen these problems before and know the patterns that work
• Expert revenue systems engineering with hands-on experience building billing platforms, payment processing, reconciliation, and managing complex challenges like idempotent transactions, payment retries, proration, multi-currency support, and revenue recognition.
• Financial systems expertise with deep experience implementing audit trails, reconciliation workflows, revenue reporting, and compliance controls at scale – you understand what it takes to maintain penny-perfect accuracy
• Java expertise with a deep understanding of JVM performance, concurrency, and operational characteristics. Scala experience is a big plus
• Experience with AI-powered development tools such as Claude Code, GitHub Copilot, or similar agentic coding tools for enhanced productivity

  Our Stack

• Languages + Frameworks: TypeScript, React, Scala (principally), Java (limited)
• Datastores: MySQL, PostgreSQL, Snowflake
• Cloud: AWS
• Version control: Git & GitHub
• AI Tooling: Copilot on GitHub and Claude Code
• Observability: Datadog

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection.

When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $220,000 USD to $250,000 USD annually. The actual base pay offered is determined by several variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base pay is one component of Metropolis's total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans, and more.

Machine Learning Engineer - LLMs & Generative AI

Truveta is the world’s first health provider led data platform with a vision of Saving Lives with Data. Our mission is to enable researchers to find cures faster, empower every clinician to be an expert, and help families make the most informed decisions about their care. Achieving Truveta’ s ambitious vision requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values.

This position is based out of our headquarters in the Greater Seattle area.  #LI-hybrid

Who We Need 

Truveta is building a diverse and inclusive team to tackle complex health and technical challenges. We are seeking enthusiastic new graduates who are problem-solvers, collaborative teammates, and eager to make a difference in healthcare. If you’re excited about purposeful work, joining a mission-driven team, and launching your career in a supportive environment, Truveta could be the perfect place to start.

This Opportunity 

We are looking for a Machine Learning Engineer with a deep background in generative AI, large language models (LLMs), and reinforcement learning techniques to build the next generation of AI systems for trustworthy healthcare. This role offers a unique opportunity to build foundational models trained on vast clinical data and drive innovation in a highly meaningful domain.

Responsibilities

• Lead the development, training, and deployment of large language and multimodal foundation models tailored to clinical and biomedical domains.
• apply and refine state-of-the-art techniques such as supervised fine-tuning (SFT), reinforcement learning-based methods (e.g., RLHF, RLVR), parameter-efficient fine-tuning (PEFT), prompt tuning, and retrieval-augmented generation (RAG).
• Collaborate cross-functionally with researchers, clinicians, and engineers to design ML-driven solutions that improve healthcare delivery and outcomes.
• Build scalable infrastructure for distributed training of large models (TPU/GPU clusters, multi-node orchestration).
• Design and evaluate models for robustness, bias mitigation, factual consistency, and explainability in healthcare contexts.
• Stay current with the latest research in generative AI and contribute back to the community through publications and open-source initiatives.

Minimum Qualifications

• 6+ years of experience in software engineering or machine learning (3+ years with a PhD).
• Experience designing and training LLMs or large-scale generative models (e.g., GPT, PaLM, LLaMA, Claude, Gemma).
• Deep expertise in NLP, sequence modeling, and transformer architectures.
• Proficient in Python and ML libraries such as PyTorch or TensorFlow; strong engineering skills in building scalable ML pipelines.
• Experience with RL-based fine-tuning (e.g., Reinforcement Learning from Human Feedback) and evaluation of generative systems.
• Proven ability to lead technical projects and collaborate across teams.
• Bachelor's degree in Computer Science, Engineering, or a related technical field

Preferred Qualifications

• PhD or equivalent experience in Machine Learning, NLP, AI, or a related field.
• Experience in healthcare, biomedical informatics, or clinical data modeling.
• Familiarity with multi-modal foundation models (e.g., text-image, text-structured data) and cross-modal alignment techniques.
• Hands-on experience with vector databases, semantic search, and retrieval-based generation
• Publications in top-tier ML conferences (NeurIPS, ICML, ACL, EMNLP, ICLR, etc.).
• Experience building trustworthy AI systems and applying model interpretability, fairness, and safety frameworks.

Why Truveta?

Be a part of building something special. Now is the perfect time to join Truveta. We have strong, established leadership with decades of success. We are well-funded. We are building a culture that prioritizes people and their passions across personal, professional, and everything in between. Join us as we build an amazing company together.

We Offer:

• Interesting and meaningful work for every career stage
• Great benefits package
• Comprehensive benefits with strong medical, dental and vision insurance plans
• 401K plan
• Professional development & training opportunities for continuous learning
• Work/life autonomy via flexible work hours and flexible paid time off
• Generous parental leave
• Regular team activities (virtual and in-person)
• The base pay for this position is $155,000 to $175,000. The pay range reflects the minimum and maximum target. Pay is based on several factors including location and may vary depending on job-related knowledge, skills, and experience. Certain roles are eligible for additional compensation such as incentive pay and stock options.

If you are based in California, we encourage you to read this important information for California residents linked here.

Truveta is committed to creating a diverse, inclusive, and empowering workplace. We believe that having employees, interns, and contractors with diverse backgrounds enables Truveta to better meet our mission and serve patients and health communities around the world. We recognize that opportunities in technology historically excluded and continue to disproportionately exclude Black and Indigenous people, people of color, people from working class backgrounds, people with disabilities, and LGBTQIA+ people. We strongly encourage individuals with these identities to apply even if you don’t meet all of the requirements.

Please note that all applicants must be authorized to work in the United States for any employer as we are unable to sponsor work visas or permits (e.g. F-1 OPT, H1-B) at this time. We appreciate your interest in the position and encourage you to explore future opportunities with us.

About the role

Why this role is exciting

Why you'll love it here:

• 💰 Competitive Compensation. For this role our salary is targeted at $150-175k USD per year. Final offer amounts are determined by factors such as experience and expertise. We take a geo neutral approach to compensation within the US, meaning that we pay based on job function and level, not location. 
• 🏆  Syndio Equity. So you can share in Syndio’s success.
• 🏝 Generous vacation policy.
• 🩺  Medical, Dental, Vision.
• 📍Remote-first in the following approved U.S. states: AZ, CA, CO, CT, DC, FL, GA, ID, IL, IA, MD, MA, MN, NE, NJ, NY, OH, OR, PA, RI, SC, SD, TX, UT, VT, VA, WA, and WI.

Role Progression:

In the 1st Month:

• Complete onboarding on the Syndio platform and the "Decision Intelligence" vision.
• Master the new Integration Platform and current data loading artifacts.
• Shadow 2-3 strategic client implementations and identify potential automation opportunities.
• Contribute to a pilot migration of an existing client’s data into the new platform.

At 3 Months:

• Independently lead technical implementations for new clients.
• Execute data migrations for a segment of the existing client base into the new Integration platform.
• Build reusable "Implementation Artifacts" (scripts, prompts, templates) that reduce time-to-value for the whole team.
• Contribute to the design of our new Platform’s Implementation process, identifying automation and other artifacts to minimize the client’s time to value.

By 6 Months:

• Manage a portfolio of high-complexity implementations for Syndio’s most strategic accounts utilizing automation and other artifacts to maximize client’s value in minimum time.
• Help achieve the goal of migrating 70% of the client base to the new Integration platform solution.
• Serve as a subject matter expert for "Process Embedding," ensuring clients are fully adopting the platform’s advanced setup features.

The interview overview

Below you'll find an outline of the interview plan for our Senior Forward Deployed Engineer position. Please note that this is what we expect the process to look like; we may ask you for supplemental information or require an additional step before making a final decision.

1. 30 min phone call with a member of our Talent Team.
2. 45-60 min Zoom deep dive with the Hiring Manager (Director of Forward Deployed Engineering).
3. 45 min technical interview with a Senior Engineer to walk through your code or logic.
4. 2-3 video interviews with key members of the Customer Success and Product teams.
5. 30 min interview with the SVP of Engineering - Data Strategy.

About the role

Why this role is exciting

Why you'll love it here:

• 💰 Competitive Compensation. For this role our base salary is targeted at $99-133k CAD. Final offer amounts are determined by factors such as experience and expertise.
• 🏆 Syndio Equity. So you can share in Syndio’s success.
• 🏝 20 days annually. We encourage our team to recharge when they need to, plus paid sick & safe time, compassion leave, and voting leave. 
• 💊 Private Medical Coverage
• 🔌 Monthly Electronics Reimbursement
• 🏠 WFH Stipend
• 📍 Remote-First (within commuting distance of Calgary) #LI-Remote 

Role Progression:

In the 1st Month:

• Complete onboarding on the Syndio platform and the "Decision Intelligence" vision.
• Master the new Integration Platform and current data loading artifacts.
• Shadow 2-3 strategic client implementations and identify potential automation opportunities.
• Contribute to a pilot migration of an existing client’s data into the new platform.

At 3 Months:

• Independently lead technical implementations for new clients.
• Execute data migrations for a segment of the existing client base into the new Integration platform.
• Build reusable "Implementation Artifacts" (scripts, prompts, templates) that reduce time-to-value for the whole team.
• Contribute to the design of our new Platform’s Implementation process, identifying automation and other artifacts to minimize the client’s time to value.

By 6 Months:

• Manage a portfolio of high-complexity implementations for Syndio’s most strategic accounts utilizing automation and other artifacts to maximize client’s value in minimum time.
• Help achieve the goal of migrating 70% of the client base to the new Integration platform solution.
• Serve as a subject matter expert for "Process Embedding," ensuring clients are fully adopting the platform’s advanced setup features.

The interview overview

Below you'll find an outline of the interview plan for our Forward Deployed Engineering position. Please note that this is what we expect the process to look like; we may ask you for supplemental information or require an additional step before making a final decision.

1. 30 min phone call with a member of our Talent Team.
2. 45-60 min Zoom deep dive with the Hiring Manager (Director of Forward Deployed Engineering).
3. Technical/Strategic Evaluation: A take-home or live case study focusing on:
• Designing a data ingestion plan for a complex client.
• Demonstrating how you leverage AI prompting to solve an implementation exception.
• Creating a "theoretical" plan for group setup and user adoption.
4. 45 min technical interview with a Senior Engineer to walk through your code or logic.
5. 2-3 video interviews with key members of the Customer Success and Product teams.
6. 30 min interview with the SVP of Engineering - Data Strategy.

Sr SWE -AI

Senior Software Engineer, AI Platform (Corporate AI Team)

Team & Role Overview

Axon’s Corporate AI Team sits within the Enterprise Data organization and focuses on internal-facing AI solutions that help Axon employees do more high‑value work with less manual effort. The team builds and operates Cortex, Axon’s internal AI platform that provides GPT‑class models, chat assistants, and secure integrations with systems like Quip, Jira, Slack, Microsoft 365, Snowflake, and more.
We’re looking for a Senior Software Engineer, AI Platform to help design, build, and scale this platform. In this role, you’ll:

• Own core services and integrations that power AI experiences for thousands of Axon employees.
• Collaborate with Corporate AI, Data Engineering, and business teams to turn real workflows into secure, reliable AI‑powered tools.
• Help define best practices and patterns for building production‑grade LLM and agentic workloads at Axon.

This is a hands‑on senior IC role—you’ll spend most of your time designing, coding, and operating production systems, not managing people.

What You’ll Do

Build and Evolve the AI Platform

• Design, build, and operate services that power Axon’s internal AI platform (Cortex), including chat experiences, agents, and integrations with enterprise systems.
• Implement and standardize patterns for deploying AI‑driven applications (APIs, web services, workflows, agents) across Axon’s cloud environments.
• Own and extend connectors and MCP integrations (e.g., Jira, Quip, Slack, M365, Snowflake) that allow LLMs to safely read and write data in Axon systems.
• Measure and improve reliability, latency, and cost for AI workloads, using telemetry and feedback from real users.

Deployment, Integration, and Reliability

• Drive the end‑to‑end lifecycle of new AI features—from prototype to hardened production service (design, implementation, testing, rollout, and operations).
• Evaluate new AI services (e.g., OpenAI, AWS Bedrock, Azure ML) for fit, performance, and cost; recommend and implement the right options for each use case.
• Implement monitoring, alerting, and auditing for AI services, ensuring we can trace usage, detect anomalies, and keep systems healthy in production.

Enablement, Best Practices, and Architecture

• Help define and document best practices for GPT/LLM solution development, including prompt engineering, RAG patterns, agentic workflows, and safe tool use.
• Partner with Corporate AI and Enterprise Architects to shape reference architectures for AI‑enabled apps and workflows (scalability, resiliency, observability, data access).
• Contribute to internal starter kits, training content, and templates that help other engineers and analysts build on the platform effectively.

Security, Governance, and Responsible AI

• Implement and maintain secure patterns for API key management, secrets, and access to models and data sources, aligned with Axon’s security and compliance standards.
• Work with Data, Security, and Governance partners to operationalize responsible AI guardrails—e.g., model selection, data minimization, logging, and usage controls.
• Ensure that new capabilities respect permissions, auditing, and policy requirements across systems like Jira, Quip, Slack, M365, and Snowflake.

Collaboration and Communication

• Collaborate closely with Data Engineering, Solution Architecture, and business teams (Finance, Sales, Operations, etc.) to turn real workflows into repeatable AI solutions.
• Clearly communicate design decisions, trade‑offs, and status to technical and non‑technical stakeholders.
• Participate in brainstorming and discovery sessions to identify “big dumb problems worth solving” with AI and automation.

What You Bring

• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
• 4+ years of professional software engineering experience, including building and operating production services or platforms.
• Strong proficiency in at least one of: Python, TypeScript/JavaScript, or Java.
• Experience with at least one major cloud provider (AWS, Azure, or GCP) and comfort working with cloud‑native services (functions, containers, managed databases, queues, storage).
• Solid understanding of web service fundamentals (APIs, authentication/authorization, observability, CI/CD) and how to build reliable, maintainable systems.
• Demonstrated interest in AI/ML and LLMs—for example, integrating with OpenAI, Bedrock, or similar APIs; building GPT‑style apps; or using AI‑assisted development tools.
• Basic understanding of security best practices (secrets management, least‑privilege access, audit logging) and eagerness to deepen this in the context of AI platforms.
• Strong communication and collaboration skills, with comfort working in a fast‑moving, experimental environment.

Preferred Experience

You don’t need all of these, but experience in several of the following will help you ramp quickly:

• Hands‑on work with LLM platforms and tools, such as OpenAI (ChatGPT / APIs), AWS Bedrock, Azure OpenAI, or Azure ML Studio.
• Experience integrating with enterprise systems like Jira, Confluence/Quip, Slack, M365, Salesforce, or Snowflake—especially via APIs or connectors.
• Familiarity with RAG (Retrieval‑Augmented Generation), semantic search, or vector stores in production contexts.
• Exposure to DevOps / platform engineering: Terraform or similar IaC, GitHub Actions or other CI/CD systems, containerization (Docker, Kubernetes), and application monitoring stacks.
• Experience building internal platforms or self‑service tools used by multiple teams.
• Participation in enablement activities (internal trainings, office hours, documentation, or community programs like Axon’s Champions Circle) is a plus.

AI Software Engineer – Cloud AI Platforms

At NICE, we are not just building software—we are transforming how cloud operations are run using AI. We are building intelligent platforms that can understand system behavior, make decisions, and automate real-world operational workflows at scale. If you’re excited about applying AI beyond chatbots into real production systems, this is an opportunity to work on meaningful, high-impact problems.

What’s the role all about?

As an AI Software Engineer, you will be part of a team building AI-powered operational platforms that integrate across monitoring systems, CI/CD pipelines, ticketing tools, and cloud infrastructure. You will work on designing and implementing intelligent workflows, integrating AI models, and building scalable systems that automate complex operational tasks.

This is a highly hands-on role focused on building, integrating, and scaling AI-driven solutions in production environments.

How will you make an impact?

• Build and scale AI-driven workflows and automation systems
• Develop integrations with systems like monitoring platforms, ticketing tools (ServiceNow, Jira, OpsGenie), CI/CD pipelines, and cloud services
• Design and implement APIs, tools, and data pipelines that power AI-driven decision-making
• Work on LLM integrations, prompt engineering, and orchestration layers — streaming responses, function calling, tool use, RAG pipelines, agentic orchestration
• Build and maintain full-stack AI applications using TypeScript, React, and Next.js — from user dashboards and personalized experiences to real-time analytics and interactive tools
• Translate real-world operational problems into automated, intelligent solutions
• Collaborate with Product, SRE, and Infrastructure teams to deliver end-to-end capabilities
• Improve system performance, reliability, and observability
• Build evaluation and observability systems — measure model capabilities, monitor output quality, and create dashboards that keep the product improvable
• Create reusable platforms and tools that accelerate development — component libraries, shared abstractions, internal tooling that multiplies team productivity

Key Responsibilities

• Design and develop scalable backend systems for AI-powered platforms
• Build and maintain AI integrations, workflows, and automation pipelines
• Implement REST APIs, microservices, and event-driven architectures
• Design and implement database schemas and queries for complex domains — tracking, engagement, reporting
• Work with both structured and unstructured data for AI use cases
• Contribute to CI/CD pipelines, testing, and deployment automation
• Troubleshoot and optimize production systems
• Collaborate with cross-functional teams to deliver high-quality solutions
• Contribute to reusable frameworks and engineering best practices
• Prototype fast — move from concept to working demo in days, ship incrementally

What we’re looking for

• 5+ years of software engineering experience, strong focus on full-stack web development
• Expert in TypeScript and React — performance optimization, modern patterns (hooks, context, suspense), component architecture
• Production experience with Next.js — App Router, Server Components, API routes, SSR/SSG, edge deployment
• Hands-on experience with LLMs — prompt engineering, streaming APIs, function calling, tool-use, chaining and orchestration patterns
• Experience with Vercel AI SDK — unified LLM provider interface, streaming, structured output, tool calling across OpenAI/Anthropic/Google/xAI
• Model Context Protocol (MCP) — building or consuming MCP servers for extensible AI tool use
• Strong backend fundamentals — Node.js or Python, REST/GraphQL APIs, relational databases, Redis, auth
• Solid database design — PostgreSQL, Drizzle ORM, schema modeling for complex domains, query optimization, migrations
• Experience building scalable, distributed systems in cloud environments (AWS / Azure)
• Working knowledge of CI/CD, Docker, Kubernetes
• Familiarity with Tailwind CSS, Radix UI and modern component-driven UI development
• High agency — you operate independently in ambiguous environments, take ownership of problems, and drive them to completion
• Strong problem-solving and analytical skills
• Ability to work in a fast-paced, evolving environment
• Communicate effectively with both technical and non-technical stakeholders

Nice to have

• Experience building agentic coding tools, AI agent frameworks, or developer-facing SDKs/APIs (Claude Agent SDK, OpenAI Agents SDK)
• Experience with Vercel ecosystem — Next.js, AI SDK providers, Turbopack
• Background in evaluation frameworks — measuring model capabilities, collecting human feedback at scale, A/B testing outputs
• Experience with sandboxed execution environments for safely running AI-generated code
• Built research tools, experimentation platforms, or scientific software
• Proficiency with Python — FastAPI/Django, data pipelines, ML tooling
• Knowledge of observability tools (Grafana, Prometheus, Sentry, etc.)
• Experience building automation or internal platforms
• Familiarity with real-time features — WebSockets, streaming UX, collaborative interfaces
• Knowledge of advanced web technologies — WebGL, WebAssembly, web workers, PWAs
• Experience with alternate JS runtimes — Bun, Deno
• Built open-source tools or platforms with active user communities
• Strong quantitative foundation (math, physics, or related fields)

Representative Projects

Things you might build in this role:

• Interfaces for collecting and managing human feedback on model outputs at scale
• Experiment orchestration platforms — launch, monitor, and analyze complex AI research runs
• Visualization tools that help understand model behavior and identify failure modes
• Reusable components and frameworks that enable rapid development of new AI applications
• Sandboxed execution environments for safely running AI-generated code
• AI-powered personalization engines — tutoring, content generation, adaptive features
• Workflow builders that let non-engineers orchestrate AI capabilities visually
• Enterprise integrations — ServiceNow, Salesforce, Confluence, Jira

The Role

We’re looking for an Applied AI Engineer to help build the next generation of agentic systems. This role combines deep software engineering skills with an experimental mindset around how AI can be practically applied to solve real user problems.

You’ll collaborate across product, research, and engineering to design agents that reason, interact with environments and evolve through feedback. Ideal candidates bring curiosity, a love of ambiguous problems, and hands-on experience applying LLMs in production.

What You'll Own

• Build autonomous and semi-autonomous agent workflows that interact with browsers, codebases, and APIs to complete complex content operations.
• Evaluate model behavior in live environments and pioneer approaches for applying reinforcement learning to end-to-end agent systems.
• Design modular frameworks for tools, memory, and evaluators to enable continuous learning and improvement of agents.
• Develop data pipelines to collect, transform, and annotate real-world usage data for SFT and RL training.
• Design and build proprietary agent libraries, prompting strategies and benchmarking frameworks.
• Partner with customers and internal stakeholders to understand edge cases and align AI behaviors with user expectations.

What We're Looking For

• 4+ years of software engineering experience, with at least a year working directly on AI/ML-powered applications. 
• Strong fluency in AI tooling (e.g. OpenAI APIs, Anthropic APIs). 
• Practical understanding of LLMs, prompt engineering and agentic architectures.
• Experience building production systems that integrate external environments - code execution, browser automation or API orchestration.
• High degree of ownership and comfort in experimental, fast-moving environments.

Nice to Have

• Familiarity with benchmarks like SWE-bench or evaluation strategies for tool-using agents.
• Exposure to customer-facing roles or user research for AI product development.
• Background in reinforcement learning or data-centric AI approaches.

Compensation

The salary range for this position is $130,000 – $220,000 annually. Final compensation will be determined based on factors such as experience, skills, and qualifications. In addition to base salary, this role may be eligible for performance-based bonuses and equity awards. Gradial offers a comprehensive benefits package, including medical, dental & vision insurance, 401K retirement plan, paid time off, paid sick leave and other employee wellness programs. 

About the Role:

As a member of the Product and Engineering team at PitchBook, you will be part of a team of big thinkers, innovators, and problem solvers who strive to deepen the positive impact we have on our customers and our company every day. We value curiosity and the drive to find better ways of doing things. We thrive on customer empathy, which remains our focus when creating excellent customer experiences through product innovation.

We know that greatness is achieved through collaboration and diverse points of view, so we work closely with partners around the globe. As a team, we assume positive intent in each other’s words and actions, value constructive discussions, and foster a respectful working environment built on integrity, growth, and business value. We invest heavily in our people, who are eager to learn and constantly improve. Join our team and grow with us!

As a member of the Product and Engineering organization, you will join a team of builders, innovators, and problem solvers focused on amplifying the impact of AI across PitchBook. We value curiosity, pragmatic experimentation, and a relentless focus on improving how teams work.

As a Senior Software Development Engineer, AI Enablement, you will serve as a senior individual contributor and force multiplier for engineering, product, research, and business teams by designing and building AI-powered developer productivity and general productivity tools. Your mission is to reduce friction, accelerate delivery, and embed AI as a natural extension of everyday work across the company.

Rather than focusing on core infrastructure ownership, this role emphasizes internal platforms, developer tools, workflows, and enablement patterns that help teams build, ship, and operate faster using AI. You will work closely with engineers, product managers, and non-technical partners to translate ambiguous, real-world pain points into scalable, high-impact solutions.

In this senior role, you are expected to operate with a high degree of autonomy, lead complex initiatives end-to-end, and raise the technical bar through strong design, implementation, and mentorship. Your work will directly influence how PitchBook teams use Generative AI, LLMs, and automation to create value—helping the company move faster, innovate more effectively, and fully realize the benefits of its AI investments.

Primary Job Responsibilities:

• Act as a senior technical force multiplier by building AI-powered tools, workflows, and “golden paths” that significantly accelerate delivery and reduce cognitive and operational overhead
• Design, implement, and iterate on internal AI-enabled productivity tools (e.g., coding assistants, research accelerators, workflow automation, decision-support tools) used by teams across the company
• Lead the technical design and execution of complex AI enablement initiatives, from problem discovery through production adoption
• Partner deeply with engineering, product, and business teams to identify high-impact opportunities where AI can meaningfully improve speed, quality, or scale
• Build reusable software components, libraries, and reference implementations that make AI easy, safe, and consistent to adopt
• Set and uphold high standards for code quality, system design, reliability, and maintainability
• Collaborate in an Agile environment with engineers, product managers, and cross-functional stakeholders
• Provide technical leadership through code reviews, design reviews, mentorship, and hands-on collaboration
• Own projects end-to-end with minimal oversight, making sound technical and product trade-offs
• Continuously evaluate emerging AI tools, frameworks, and best practices and translate them into practical internal capabilities
• Champion responsible, secure, and scalable AI usage across the organization
• Support PitchBook’s culture and values by modeling curiosity, collaboration, ownership, and continuous improvement
• Contribute to the evolution of PitchBook’s AI capabilities and enablement strategy
• Support the vision and values of the company through role modeling and encouraging desired behaviors 
• Participate in various company initiatives and projects as requested 

Skills and Qualifications:

• Degree in Computer Science, Software Engineering, or a related field
• 5+ years of professional software development experience with demonstrated ownership of complex systems
• Strong proficiency in Python (experience with JavaScript/TypeScript or Java is a plus)
• Hands-on experience building developer tools, internal platforms, or productivity-focused software used by other engineers
• Practical experience working with Generative AI and LLMs (e.g., OpenAI APIs, LangChain, or similar frameworks)
• Experience integrating AI into real-world, production workflows rather than purely experimental prototypes
• Solid understanding of prompt engineering, evaluation techniques, and responsible AI patterns
• Experience designing APIs, services, or libraries consumed by multiple teams
• Comfort working with SQL and/or NoSQL databases
• Strong understanding of Git, CI/CD workflows, testing strategies, and modern development practices
• Proven ability to operate in ambiguous problem spaces and independently identify high-leverage opportunities
• Strong communication and stakeholder collaboration skills with the ability to explain complex technical concepts clearly
• Track record of mentoring other engineers and raising the technical bar on a team
• Must be authorized to work in the United States without the need for visa sponsorship now or in the future

Benefits + Compensation at PitchBook:

Physical Health

• Comprehensive health benefits
• Additional medical wellness incentives
• STD, LTD, AD&D, and life insurance

Emotional Health

• Paid sabbatical program after four years
• Paid family and paternity leave
• Annual educational stipend
• Ability to apply for tuition reimbursement
• CFA exam stipend
• Robust training programs on industry and soft skills
• Employee assistance program
• Generous allotment of vacation days, sick days, and volunteer days

Social Health 

• Matching gifts program
• Employee resource groups
• Subsidized emergency childcare
• Dependent Care FSA
• Company-wide events
• Employee referral bonus program
• Quarterly team building events

Financial Health 

• 401k match
• Shared ownership employee stock program
• Monthly transportation stipend

*Please be aware the above PitchBook benefit and perk offerings are subject to corresponding plan and policy documents and may change during the course of your employment.

Compensation

• Annual base salary: $160,000-$200,000
• Target annual bonus percentage: 10%

Working Conditions:

At the heart of our company is a belief in the power of in-person collaboration. Being together in the office fuels our creativity, strengthens our connections, and drives the innovation that sets us apart. Our culture is built on spontaneous moments—those hallway conversations, whiteboard brainstorms, and shared celebrations in each of our global offices—that simply can’t be replicated remotely. This role is expected to be in the office 5 days a week.

The job conditions for this position are in a standard office setting. Employees in this position use PC and phone on an on-going basis throughout the day. Limited corporate travel may be required to remote offices or other business meetings and events.

We are excited to get to know you and your background. Concerned that you might not meet every requirement? We encourage you to still apply as you might be the right candidate for the role or other roles at PitchBook.

#LI-KL1

#LI-Onsite

About the Role:

As a member of the Product and Engineering team at PitchBook, you will be part of a team of big thinkers, innovators, and problem solvers who strive to deepen the positive impact we have on our customers and our company every day. We value curiosity and the drive to find better ways of doing things. We thrive on customer empathy, which remains our focus when creating excellent customer experiences through product innovation.

We know that greatness is achieved through collaboration and diverse points of view, so we work closely with partners around the globe. As a team, we assume positive intent in each other’s words and actions, value constructive discussions, and foster a respectful working environment built on integrity, growth, and business value. We invest heavily in our people, who are eager to learn and constantly improve. Join our team and grow with us! 

As a Staff Software Development Engineer, AI Enablement, you will operate as a technical leader and force multiplier across Product, Engineering, Research, and Business teams. Your role is to define, build, and scale AI-powered productivity capabilities that fundamentally change how PitchBook teams work, ship, and innovate. 

This is a high-impact, high-autonomy role focused on software systems, internal platforms, and developer productivity tools, rather than core infrastructure ownership. You will identify the highest-leverage opportunities for AI enablement, set technical direction, and deliver reusable solutions that accelerate delivery, improve quality, and reduce friction across the organization. 

You will partner closely with engineering leaders, product leaders, and executive stakeholders to ensure AI is embedded into workflows in a safe, scalable, and repeatable way. Your work will directly influence PitchBook’s ability to move faster than competitors, fully realize the value of AI investments, and attract and retain top technical talent. 

Primary Job Responsibilities:

• Act as a technical force multiplier at the organizational level, designing AI-powered tools and workflows that unlock step-change productivity gains 
• Define and own the technical vision and roadmap for internal AI enablement and developer productivity capabilities 
• Architect and build scalable internal platforms, libraries, and “golden paths” that make AI easy, safe, and effective to adopt 
• Identify systemic bottlenecks in development, research, and knowledge workflows and translate them into high-impact AI solutions 
• Lead complex, ambiguous initiatives end-to-end, from problem framing and experimentation through production adoption 
• Partner with senior engineers, managers, product leaders, and non-technical stakeholders to align solutions with business priorities 
• Establish best practices, patterns, and standards for AI usage across teams, including quality, safety, and evaluation 
• Provide technical leadership through design reviews, mentorship, and hands-on collaboration across multiple teams 
• Evaluate emerging AI technologies and translate them into practical, production-ready capabilities 
• Champion responsible AI usage, scalability, and long-term maintainability 
• Model PitchBook’s values by fostering a culture of curiosity, collaboration, and continuous improvement 
• Support the vision and values of the company through role modeling and encouraging desired behaviors 
• Participate in various company initiatives and projects as requested 

Skills and Qualifications:

• Degree in Computer Science, Software Engineering, or related field (or equivalent experience) 
• 8+ years of professional software development experience, with demonstrated impact at scale 
• Proven experience leading cross-team technical initiatives or internal platforms 
• Deep proficiency in Python; experience with additional languages (e.g., JavaScript/TypeScript, Java) is a plus 
• Strong hands-on experience building AI-enabled products or productivity tools using LLMs and GenAI frameworks 
• Experience designing APIs, shared services, or developer platforms used by multiple teams 
• Strong understanding of prompt engineering, evaluation strategies, and responsible AI patterns 
• Experience translating ambiguous business problems into scalable technical solutions 
• Solid grounding in modern development practices (Git, CI/CD, testing, observability) 
• Excellent communication skills with the ability to influence without authority 
• Track record of mentoring senior engineers and raising the technical bar across teams 
• Must be authorized to work in the United States without the need for visa sponsorship now or in the future

Benefits + Compensation at PitchBook:

Physical Health

• Comprehensive health benefits
• Additional medical wellness incentives
• STD, LTD, AD&D, and life insurance

Emotional Health

• Paid sabbatical program after four years
• Paid family and paternity leave
• Annual educational stipend
• Ability to apply for tuition reimbursement
• CFA exam stipend
• Robust training programs on industry and soft skills
• Employee assistance program
• Generous allotment of vacation days, sick days, and volunteer days

Social Health 

• Matching gifts program
• Employee resource groups
• Subsidized emergency childcare
• Dependent Care FSA
• Company-wide events
• Employee referral bonus program
• Quarterly team building events

Financial Health 

• 401k match
• Shared ownership employee stock program
• Monthly transportation stipend

*Please be aware the above PitchBook benefit and perk offerings are subject to corresponding plan and policy documents and may change during the course of your employment.

Compensation

• Annual base salary: $185,000 - $240,000
• Target annual bonus percentage: 15%

Working Conditions:

At the heart of our company is a belief in the power of in-person collaboration. Being together in the office fuels our creativity, strengthens our connections, and drives the innovation that sets us apart. Our culture is built on spontaneous moments—those hallway conversations, whiteboard brainstorms, and shared celebrations in each of our global offices—that simply can’t be replicated remotely. This role is expected to be in the office 5 days a week.

The job conditions for this position are in a standard office setting. Employees in this position use PC and phone on an on-going basis throughout the day. Limited corporate travel may be required to remote offices or other business meetings and events.

We are excited to get to know you and your background. Concerned that you might not meet every requirement? We encourage you to still apply as you might be the right candidate for the role or other roles at PitchBook.

#LI-KL1

#LI-Onsite

Responsibilities:

• Help secure AI products and internal tools that are introducing industry-novel security risks and pushing established security boundaries
• Lead “shift left” security efforts to build security into the software development lifecycle.
• Conduct secure design reviews and threat modeling. Identify and prioritize risks, attack surfaces, and vulnerabilities.
• Develop tooling to scale security code reviews and respond to developer questions, including advising developers on remediating vulnerabilities and following secure coding practices. 
• Manage Anthropic's vulnerability management program, including integrating data ingestion pipelines, coding logic to prioritize vulnerability fixes, supporting teams remediating vulnerabilities and developing automated systems at scale.
• Oversee Anthropic's bug bounty program. Set scope, validate submissions, perform root cause analysis, coordinate remediation with engineering teams, and award bounties. Cultivate relationships with the ethical hacker community.
• Collaborate closely with product engineers and researchers to instill security best practices. Advocate for secure architecture, design, and development.
• Develop and document security policies, standards, and playbooks. Conduct security awareness training for engineers.

You may be a good fit if you:

• Have 5+ years of hands-on experience in application and infrastructure security, including securing cloud-based and containerized environments.
• Strong proficiency in at least one programming language (e.g., Python, Rust, Go, Java)
• Lead with empathy, a collaborative spirit, and a learning mindset to work cross-functionally with engineers of all levels to build security into the software development life cycle.
• Leverage creative and strategic thinking to reduce risk through secure design and simplicity, not just controls.
• Possess broad security knowledge to connect the dots across domains and identify holistic ways to decrease the overall threat surface.
• Are keen to distill complex security concepts into clear actions and drive consensus without direct authority.
• Embody a proactive mindset to thread security throughout the product lifecycle through activities like threat modeling, secure code review, and education.
• Have a strong grasp of offensive security to anticipate risks from an adversary's perspective, not just check compliance boxes.
• Bring experience with modern application stacks, infrastructure, and security tools to implement pragmatic defenses.
• Are practiced at collaborating cross-functionally and effectively balancing security requirements with business objectives.
• Advocate for security fundamentals like least privilege, defense-in-depth, and eliminating complexity that could sub-linearly scale security through smart design.

Strong candidates may also:

• Hands-on technical expertise securing complex cloud environments and microservices architectures leveraging technologies like Kubernetes, Docker, and AWS / GCP.
• Exposure to offensive security techniques like vulnerability testing, bug bounty, pen testing, and red team exercises. 
• Familiarity with AI/ML security risks such as prompt injection, data poisoning, model extraction, etc. and mitigations.
• Experience building security tools, applications, and automated tools.
• Solid foundational knowledge of both software and security engineering principles and are keen to continue learning.
• Excellent communication skills, able to distill complex security topics for broad audiences.
• Worked and thrived in fast-paced environments, and comfortable navigating ambiguity.

As a Senior Gen AI Engineer, Salesforce Platform you will lead the development of AI-powered solutions across our Salesforce platform to streamline end-to-end business operations. Partnering with the Manager of Salesforce Operations and the Principal AI Architect, you will implement orchestrated AI agents using Salesforce Einstein, Agentforce, and DataCloud, and deliver secure, scalable solutions via Apex, Visualforce, Lightning Web Components, and robust APIs.

You will leverage generative AI to enhance efficiency, reduce manual work, and create smarter systems and workflows across our organization.  Candidates with a deep understanding of business operations and workflows are strongly preferred.  You will play a critical role in delivering AI solutions and frameworks that drive transformative business value.  This is a unique opportunity for full-stack development to experiment and solve for multiple use cases, as well as an opportunity to help educate business stakeholders on the power of AI solutions.

You will: 

• Design, develop, and deploy generative AI solutions that modernize business operations—automating workflows, surfacing insights, and delivering intelligent recommendations with a balance of speed, functionality, and long-term scalability.
• Build, integrate, and operationalize AI agents and automations using Salesforce Agentforce (skills, actions, orchestration, guardrails) embedded within Sales, Service, and CPQ workflows.
• Implement Einstein/Agentforce solutions, including prompt flows, tools, and custom actions grounded in Salesforce Data Cloud for personalized retrieval and contextual experiences.
• Develop and secure APIs (REST/SOAP, Platform Events, Pub/Sub) to connect Salesforce with internal and external systems such as CPQ, CLM, provisioning, licensing, ERP, and finance platforms.
• Engineer data interoperability across systems—collaborating with architects and data teams to break down silos, build ETL pipelines, and establish automated data workflows.
• Build and deploy retrieval-augmented generation (RAG) patterns within Salesforce, implementing data indexing, grounding, safety measures, and evaluation loops.
• Collaborate closely with the Principal Architect and Principal AI Engineer to translate high-level business objectives into production-ready AI-powered solutions, ensuring alignment with architectural and engineering best practices.
• Prototype rapidly to validate new generative AI use cases and transition successful proofs-of-concept into stable, scalable, maintainable production applications.
• Contribute to full-stack development efforts—from API design to front-end UI—when implementing AI features across various business systems.
• Drive and contribute to CI/CD pipelines, code reviews, and release management using modern tooling (SFDX, GitHub Actions, Azure DevOps, etc.).
• Ensure compliance, data security, and governance across all AI and integration solutions, including considerations for PII, data residency, consent management, and auditability.
• Partner with business stakeholders (technical and non-technical) to understand requirements, gather feedback, and continuously improve AI-driven capabilities.
• Work alongside data scientists and AI specialists to evaluate and optimize prompt strategies, fine-tune models, and implement organization-specific AI enhancements.
• Lead knowledge sharing and enablement, mentoring teams and fostering adoption of AI technologies throughout the organization.
• Monitor, evaluate, and iterate on AI solution performance to ensure quality, accuracy, and measurable business value.
• Stay current on industry advancements in AI, automation, and Salesforce innovation, integrating relevant learnings into the organization’s technology roadmap.

What We’re Looking For: 

• Bachelor’s degree in computer science, Engineering, or a related field.
• 8+ years of Salesforce engineering experience and 3+ years delivering AI or automation solutions at scale within enterprise environments.
• Proven success modernizing legacy Salesforce orgs and implementing scalable architectures across Sales Cloud, Service Cloud, and Revenue (CPQ).
• AI & Automation:
  • Hands-on experience with Salesforce Einstein, Agentforce, and Data Cloud; practical AI engineering skills in prompt design, tool calling, RAG/grounding, evaluation, guardrails, and observability.
• Technical Skills:
  • Apex, Lightning Web Components (LWC), SOQL/SOSL, and Visualforce (for legacy support).
  • Proficiency in Python for AI service development, including FastAPI/Flask APIs, evaluation scripts, and LLM endpoint integration.
  • Strong API design and integration experience with Salesforce (bi-directional, streaming, and external APIs).
  • CI/CD experience using SFDX and modern tooling (GitHub Actions, Azure DevOps, etc.).
  • Familiarity with Azure or AWS cloud environments.
• Data Architecture:
  • Experience designing and managing data across Salesforce, Data Cloud, and other business systems including identity resolution, data sharing, and segment activation.
• Operational & Business Acumen:
  • Skilled in process mapping, workflow design, and identifying operational inefficiencies to enable AI-driven improvements.
• Change Enablement:
  • Experience driving adoption and integration of AI solutions across business functions.
• Excellent communication and presentation abilities with technical and non-technical stakeholders, including executives.
• Strong problem-solving, analytical, and troubleshooting capabilities.
• Collaborative, consultative mindset with the ability to translate business needs into technical solutions.
• Comfortable working autonomously in fast-paced, evolving environments.
• Embodies the principles of the Ideal Team Player: humble, hungry, and smart.
• Certifications:
  • • Required:
      • Salesforce Certified Platform Developer I & II.
    • Preferred:
      • JavaScript Developer I, Platform App Builder, Salesforce Certified Data Cloud Consultant or Platform Data Architect, and Salesforce Certified Integration Architect.
      • Trailhead Superbadges or credentials (Agentforce, Apex Specialist, Data Cloud)

Pay Range: $154,300-216,000

Other compensation: Bonus Eligible 

Perks & Benefits:  

💻 Remote work 

✈️ Travel expected 4-8 times per year for company-sponsored events 

🩺 Medical, dental, vision, life, and disability insurance 

📈 401K retirement plan; flexible spending and health savings account 

🏝️ 15 days of paid time off + additional front-loaded personal days 

🏖️ 14 company-recognized holidays + paid volunteer days  

👶 up to 8 weeks of paid parental leave + 10 weeks of paid bonding leave  

🌈 LGBTQ+ Health Services 

🐶 Pet insurance  

📣 Check out more of our benefits here: https://www.mcg.com/about/careers/benefits/  

 Remote with Moderate Travel (4- 8 trips per year) 

This is a remote position, and does require occasional travel, typically between 4-8 times per year. All travel expenses will be covered in accordance with company policy. 

The ideal candidate should be comfortable balancing the independence of remote work with the collaborative opportunities offered by periodic in-person engagements. 

We embrace diversity and equal opportunity and are committed to building a team that represents a variety of backgrounds, perspectives, and skills. Only with diverse thoughts and ideas will we be able to create the change we want in healthcare. The more inclusive we are, the better our work will be for it.