Ai Agent Engineer in United States

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE: Voice is becoming the internet’s next interface, but a production-grade Voice AI system is "hard to build" . You’ll join a small founding team of Baseten Voice AI, focused on bringing state-of-the-art open source models into production for Voice AI customers across productivity, customer service, clinical conversation, creator tools, education, and more. You’ll make a meaningful impact on people’s daily lives and help reshape these industries. This is a high-impact, high-ownership role. You will be the primary owner of Baseten Voice AI - our in-house inference stack to power Voice AI models - from product roadmap through engineering implementation. You’ll partner closely with Forward Deployed Engineers, Model Performance Engineers, and sister engineering teams to push the boundaries of Voice AI. EXAMPLE INITIATIVES: Develop world-class model serving stack for state-of-the-art open-source voice models - reduce end-to-end and tail latency (p95/p99), increase throughput, and improve GPU efficiency via profiling, runtime tuning, and server-level optimizations. Build large-scale, real-time infrastructure for multi-model voice agents - orchestrate STT, TTS, and agent components with streaming I/O to meet customer SLOs. Design tight training and inference iteration loops for voice model customization - enable fast evaluation, safe rollout, and rapid experimentation for custom voice model development. Past projects:

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. At Snowflake, we are building a high-impact team to help the world's most innovative companies unlock the power of AI. As an Forward Deployed Engineer, Applied AI on our Cortex AI team, you will be a hands-on builder and a key technical partner to our most strategic customers, placing you at the forefront of the enterprise AI revolution. You won't just work with cutting-edge technology – you'll deploy it to solve real-world business problems at scale, building production-grade AI systems using Snowpark, Cortex, and our native LLM capabilities. IN THIS ROLE AT SNOWFLAKE, YOU WILL: Build Customer Solutions : Architect, build, and deploy enterprise-grade AI solutions, including sophisticated AI agents. Own the end-to-end lifecycle of your work streams – from prototype to production – directly solving customers' most complex business challenges. Own the Quality of What You Ship : Define what "good" means for the systems you build. Translate ambiguous customer goals into measurable quality metrics, evaluation frameworks, and golden datasets – then run systematic eval loops to hill-climb on agent quality, catch regressions before customers do, and continuously raise the bar on accuracy, faithfulness, and safety. Treat measurement as a first-class part of building, not an aftertho

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the Role This isn’t a typical engineering role. You won’t be embedded in a single product team or siloed in one product area. Instead, you’ll sit within Platform Engineering, own the AI-assisted coding domain, and work across all of engineering at Sentry, focused specifically on how AI coding agents participate in our software development lifecycle. For AI coding agents to work well in our repo, the internal systems they depend on need to be accessible via API, not locked behind UIs that require human interaction. Right now, many of those systems aren’t agent-ready. You’ll audit and prioritize that gap, expose those systems programmatically, and build the connections that let tools like Claude Code operate on them end-to-end. From there, the scope expands to improving the quality of AI-generated pull requests and automating the engineering work that’s important but consistently deprioritized. You will look from context engineering standpoint to see what to send to our model; you will look from harness engineering standpoint to see the tools it can use, the permissions it has, the state it carries forward, the tests it has to pass, the logs you capture, the retries, checkpoints, guardrails, and evals. You’ll work closely with the dev infrastructure team as your home base, then collaborate across every product team coding in our repo once the tooling foundation is in place. It’s a broad role with real impact, and the work you do will directly change how Sentry engineers ship software. What You’ll Do Audit Sentry’s internal developer systems and make them API-ready for AI agents. You’ll prioritize and drive the work of ex

At Linear, we're building the product development system for teams and agents. AI is fundamentally changing how software gets built, and we’re shaping the tools this new era requires. Founded in 2019, Linear has become the platform of choice for more than 40,000 companies (including OpenAI, Coinbase, and Ramp) to plan, build, and ship their products. Today, our team is distributed across North America, Europe, and Australia, and we’re continuing to grow internationally. What unites us is relentless focus, fast execution, and a deep care for software craftsmanship. We’re looking for experienced engineers who have shipped applied AI systems to production and want to define what the agent-native future looks like. We are building intelligence into the core of Linear, enabling the product to orchestrate coding, proactively move work forward, and power-up every software team. You’ll work closely with product and design to transform foundation models into structured, reliable workflows embedded deeply in the core of Linear. We care deeply about keeping Linear fast, intuitive, and opinionated—AI is no exception. Location & work mode Linear is a remote-first company, with optional co-working offices in San Francisco, New York, and London. This role is open to candidates based in the North America. You can work from anywhere within this region. We value deep focus and async collaboration, with intentional moments to connect in person through team off-sites, optional co-working, and occasional travel. What you'll do Build AI-powered product features that feel native, fast, and delightful to use Work with product and design to prototype and iterate on intelligent workflows and user interactions Design backend services to power natural language interfaces, smart suggestions, agentic workloads, and more Optimize prompts, fine-tune model behavior, and evaluate performance Help to guide our agent platform, allowing third parties to bring agents into the core Linear experience

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. The Cortex CoWork team is defining the future of AI for enterprise data. Our mission is to transform how the world’s largest enterprises interact with their data through flagship products like Snowflake (CoWork) Intelligence . As a Principal AI Engineer , you will be a technical North Star for our AI initiatives. You won't just execute on a roadmap; you will help define it. You will tackle the most complex, "frontier" problems in agentic reasoning, NL-to-SQL, and enterprise-scale RAG, ensuring our AI products are not only innovative but fundamentally reliable and scalable for the Fortune 500. What you will do in this role: Technical Strategy & Architecture: Define the long-term technical vision for Snowflake Intelligence. Lead the architectural design of multi-agent systems, complex tool-use frameworks, and self-correcting NL-to-SQL engines. Drive Industry-Leading Reliability: Move beyond simple evals to build world-class, automated "hill-climbing" infrastructure. You will establish the methodology for how Snowflake measures and guarantees LLM performance across diverse customer schemas. Cross-Functional Influence: Partner with Product and Engineering leadership to align AI capabilities with business goals. You will bridge the gap between Research (modeling) and Product

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. The Agent Infra team builds the infrastructure that runs autonomous AI agents at Roblox for millions of creators building experiences on our platform, and for thousands of Roblox engineers shipping production code every day. Agent workloads break the assumptions most infrastructure is built on. They run for hours instead of milliseconds, they're non-deterministic, they execute code nobody wrote, and they need real credentials against real systems to be useful at all. Making that safe, durable, and cost effective at Roblox’s scale is the hard problem our team is solving. As an early member of the Agent Infra team you’ll work alongside an experienced engineering team on systems that are already in front of real users, at scale, in a field that didn’t exist two years ago. You Are Early in your career : 1-3 years of professional experience or a recent grad; with strong CS fundamentals and an interest in learning infrastructure, distributed, and agentic systems. Someone who builds things: You have projects, internships, or open-source work you'd genuinely enjoy walking us through. Into AI agents. You've built something with them, even something small, and you can tell us what broke. Comfortable

About the Team Business Systems / Enterprise Platform Technology builds the internal systems, data foundations, workflow infrastructure, and enterprise platforms that help OpenAI operate at scale. The EPT AI Pod builds AI-native internal apps, MCP connectors, multi-agent workflows, and reusable platform capabilities across Finance, People, and GTM. About the Role As an Enterprise Applied AI Engineer, you will build internal apps for enterprise operations and the shared platform components those apps run on. This includes MCP connectors, multi-agent orchestration, data architecture, evals, monitoring, auditability, and governance. We’re looking for a hands-on engineer who is strong in Python, system design, enterprise integrations, data architecture, and applied AI systems. You should be excited to turn ambiguous business workflows into reliable internal products and shared infrastructure. In this role, you will: • Build internal apps for enterprise operations across Finance, People, and GTM • Build MCP connectors and enterprise integrations with strong auth, permissions, idempotency, retries, and rate-limit handling • Design end-to-end multi-agent workflows with tool routing, human approvals, audit trails, and safe action boundaries • Design data architecture for operational AI systems, including ingestion, schemas, quality checks, lineage, and governance • Build evals, monitoring, metrics, and regression tests for agentic workflows • Create reusable infrastructure, patterns, and components that other enterprise teams can build on • Partner with system owners and business owners to turn messy enterprise workflows into reliable internal products You might thrive in this role if you: • Have strong Python engineering skills for backend services, MCP connectors, agent/tool workflows, eval harnesses, and data ingestion jobs • Have strong system design skills across shared infrastructure, app architecture, reliability, and scaling • Have experience building internal apps,

About the Team The Cooperative AI team is scaling OpenAI with OpenAI. We are building a model powered knowledge system that evolves and learns as our products, systems and customers evolve. We leverage our state of the art models, technologies, and products (some external, some still in the lab) to assist or completely automate robust operations supporting both internal and external customers. We support OpenAI customers and internal partners globally, powering systems from customer support to integrity to product insights. We are a self-contained multi-disciplinary team, who enjoy a lightning fast feedback loop with customers at scale, some of whom sit just a few pods away. We iterate fast, and engineer for reliable long-term impact. We're constantly looking for the similarities and patterns in different types of work, and focus on building simple primitives, to apply world class knowledge to many domains. The work of this team exemplifies use of OpenAI technologies. We build systems so everyone can see the leverage that is possible with well designed AI-based implementations. We do this by working through internal use cases focused on Customers (specifically knowledge systems, automation systems, and automated agent systems) to prove impact, then we scale. About the Role We’re looking for a Backend Software Engineer to help architect and scale the infrastructure that powers our knowledge systems. This is a deeply technical and highly cross-functional role where you’ll build robust systems and backend services that serve as the foundation for how knowledge is created, accessed, and applied across OpenAI. In this role, you will: Design, build, and maintain backend services and APIs to support intelligent automation and knowledge systems Integrate and structure data across internal platforms, transforming it into formats optimized for use by downstream systems and AI workflows. Collaborate closely with product, research, and engineering teams to integrate OpenAI mode

About the Team The Cooperative AI team is scaling OpenAI with OpenAI. We are building an AI powered knowledge system that evolves and learns as our products, systems and customers evolve. We leverage our state of the art models, technologies, and products (some external, some still in the lab) to assist or completely automate robust operations supporting both internal and external customers. We support OpenAI customers and internal partners globally, powering systems from customer support to integrity to product insights. We are a self-contained multi-disciplinary team, who enjoy a lightning fast feedback loop with customers at scale, some of whom sit just a few pods away. We iterate fast, and engineer for reliable long-term impact. We're constantly looking for the similarities and patterns in different types of work, and focus on building simple primitives, to apply world class knowledge to many domains. The work of this team exemplifies use of OpenAI technologies. We build systems so everyone can see the leverage that is possible with well designed AI-based implementations. We do this by working through internal use cases focused on Customers (specifically knowledge systems, automation systems, and automated agent systems) to prove impact, then we scale. About the Role We’re looking for Software Engineers who're passionate about blending production-ready platform architecture with new tech and new paradigms. You’ll push the boundaries of OpenAI’s newest technologies to enable interactions and automations that are not only functional, but delightful. We value proactive, customer-centric engineers who can get the foundational details right (data models, architecture, security) in service of enabling great products. In this role, you will: Own the end-to-end development lifecycle for new platform capabilities and integrations with other systems Collaborate closely with engineers, data scientists, information systems architects, and internal customers to understand th

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role: Notion is looking for an experienced engineer who has designed and built secure software systems to help define the security foundations for our AI products. You’ll work with product and engineering teams on agent runtimes, tool permissions, retrieval, content writes, observability, and abuse-resistant design. You’ll turn product risks into clear architecture, reusable guardrails, automated tests, and production systems that help teams ship new features safely. This role is based in San Francisco. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. What You'll Achieve: Define and build security architecture for product surfaces that operate across customer workspace content, including tool execution, content writes, retrieval, permission checks, provenance, and auditability. Make the secure path the easy path for product teams by shipping reusable libraries, review patterns, test fixtures, and guardrails that prevent classes of vulnerabilities.

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role You’ll lead the Mobile AI engineering team, responsible for making Notion AI genuinely useful on phones and tablets. Mobile is where AI needs to work in the moment: when users are capturing ideas, catching up between meetings, asking questions, or trying to move work forward away from their desk. This role can be based in either San Francisco or New York City. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. What You'll Achieve Define and evolve the roadmap for Notion’s core mobile AI surfaces, including chat, capture, agent workflows, workspace Q&A, and lightweight creation flows. Take new mobile AI ideas from exploration to shipped product, using prototypes, user feedback, and product data to decide what to build next. Improve the production quality of mobile AI by identifying instrumentation gaps, reliability risks, and performance bottlenecks before they become user problems. Help the team build the right technical foundations for fas

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. AI and intelligent systems are driving the fifth paradigm shift, following previous technological revolutions like mainframes, personal computers, the internet, and mobile devices. We believe, in the foreseeable future, AI will revolutionize the FinTech industry - from how consumers understand and manage their finances, to how developers build applications and how all companies operate. The fintech industry landscape will undergo a fundamental reshape. Plaid in the FinTech AI Ecosystem Plaid is uniquely positioned to become the financial data and insights backbone for AI applications and platforms in this evolving ecosystem. We believe consumers should be able to understand and manage their financial life through conversational AI interfaces using natural language. We believe consumers should have peace of mind with a trustworthy consent and authorization manager when agents shop for them. We believe identity verification and financial fraud prevention in AI-powered products should feel seamless and embedded for the end users. The list goes on. The most important AI companies, major fintechs, and customer agent platforms are actively trying to integrate Plaid into AI-powered products and solutions t

The Agent Research and Tooling team, part of MongoDB's AI Builder Experience organization, owns the platform layer around agents: how teams author, distribute, evaluate, monitor, and improve agent skills and agent behavior. We are hiring a software engineer to build and maintain the tooling, evaluation systems, and quality gates behind MongoDB's agent skills. This is a software engineering role at the intersection of developer tooling, applied AI, and software quality. You will take loosely defined agent and tooling problems, break them into workable plans, and ship durable internal systems: command-line tools, reusable libraries, evaluation harnesses, and CI workflows. This role is open to remote work in the US or can be based out of any of our US offices. What you'll do Build and maintain agent skills and the infrastructure to validate, evaluate, publish, and maintain them Design evaluation datasets and workflows that compare agent behavior against a baseline and produce actionable quality signals Build agent metrics and observability: skill selection and routing, success and failure outcomes, tool calls, latency, and token usage Design safety and quality gates for agent-authored content: rule packs, static analysis, confidence thresholds, structured verdicts, and bounded suppression Create CLIs, libraries, and MCP integrations that other repositories adopt and that run in local development and CI Integrate tooling into GitHub Actions and other CI workflows, including secrets, annotations, exit codes, and artifacts Build code-generation quality checks, such as anti-pattern catalogs and linting for AI-generated MongoDB code Investigate real failures such as nondeterministic results, false positives, and unsafe generated guidance, and turn them into reusable improvements Collaborate with engineers, security partners, and product teams; communicate trade-offs, risks, and ownership across teams Examples of the problems you'll solve How can tests verify an agent tool's

About the Team The Codex Core Agent team builds the kernel of Codex. We own making the agent better, accelerating research, and making those improvements real in production for our users. That means working across the systems that make Codex actually function as an agent in the real world: the production performance envelope around tokens, latency, reliability, cost, and capacity; the core execution loop and interfaces that turn models into useful behavior; the shared infrastructure that enables other teams to build on Codex; and the feedback loops that turn real-world usage into better models and better agent behavior over time. About the Role We’re looking for engineers to build the infrastructure that powers Codex agents in production. This role focuses on the systems that let models safely execute code, interact with tools, complete long-running tasks, and operate reliably and efficiently at scale. You’ll design and operate the infrastructure behind sandboxed execution, orchestration, stateful workflows, app-server and SDK boundaries, and model rollouts. You’ll work at the intersection of distributed systems, developer tooling, and AI, building primitives that make Codex faster, safer, more reliable, and easier for the rest of the organization to build on. What You’ll Do Design and build execution environments for AI agents, including sandboxing, isolation, and reproducibility. Develop systems for agent orchestration across multi-step, tool-using workflows. Build infrastructure for running, testing, and debugging code generated by models. Create state and memory systems that allow agents to persist context across long-running tasks. Optimize tokens, latency, reliability, and cost across Codex’s production fleet. Support model rollouts, capacity planning, and the core tradeoffs between quality, speed, and economics to manage a fleet of frontier agents at scale. Build shared platform capabilities that unblock product teams, partner teams, and open source Codex. Yo

About the Team We're building the foundation for a new kind of AI coworker: persistent agents that have their own environments, can meet people wherever they work, and continue making progress for as long as a task requires. Our goal is to help individuals, teams, and organizations delegate meaningful work to AI—not just ask questions or complete a single turn. Our work brings together product, agent, and infrastructure capabilities across OpenAI. Together, we are creating always-on virtual coworkers that can carry context across tasks, operate through the right tools and channels, and deliver reliable results in real workplace environments. About the Role We’re looking for a full stack product engineer to shape how people discover, direct, and collaborate with AI coworkers. You’ll own product experiences end to end, spending roughly equal time building intuitive frontend surfaces and the backend systems that make agentic workflows persistent, reliable, and useful. You’ll work at the intersection of product engineering, design, agent capabilities, and enterprise readiness—turning rapidly evolving model and platform capabilities into experiences customers can understand, trust, and use every day. In this role, you will: Design, build, and ship full stack product experiences that help people and teams delegate meaningful work to persistent AI coworkers. Create intuitive frontend interfaces for directing agents, reviewing their progress, understanding their actions, and collaborating on the work they produce. Build backend APIs, services, and data models that support persistent agent state, asynchronous execution, orchestration, and progress reporting. Develop workflows that help agents access relevant context, use tools, and collaborate with people across workplace surfaces and channels. Partner with product, design, research, and engineering teams to turn shared capabilities into cohesive products. Build trust into the product through clear user controls, understanda