Ai Agent Engineer in United States

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Who You Are We're looking for innovative and passionate Machine Learning Engineers to join our team. You are someone who loves solving complex problems, enjoys the challenges of working with huge data sets, and has a knack for turning theoretical concepts into practical, scalable solutions. You are a strong team player but also thrive in autonomous environments where your ideas can make a significant impact. You love utilizing machine learning techniques to push the boundaries of what is possible within the realm of Natural Language Processing, Information Retrieval and related spaces. Most importantly, you are excited to be part of a mission-oriented high-growth startup that can create a lasting impact. You Will Conceptualize, develop, and deploy machine learning models that underpin our NLP, retrieval, ranking, reasoning, dialog and code-generation systems. Implement advanced machine learning algorithms, such as Transformer-based models, reinforcement learning, ensemble learning, and agent-based systems to continually improve the performance of our AI systems. Process and analyze large, complex datasets (structured, semi-structured, and unstructured), and use your findings to inf

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Who you are We're looking for an innovative and passionate Machine Learning Engineers to join our team. You are someone who loves solving complex problems, enjoys the challenges of working with huge data sets, and has a knack for turning theoretical concepts into practical, scalable solutions. You are a strong team player but also thrive in autonomous environments where your ideas can make a significant impact. You love utilizing machine learning techniques to push the boundaries of what is possible within the realm of Natural Language Processing, Information Retrieval and related Machine Learning technologies. Most importantly, you are excited to be part of a mission-oriented high-growth startup that can create a lasting impact. You will: Conceptualize, develop, and deploy machine learning models that underpin our NLP, retrieval, ranking, reasoning, dialog and code-generation systems. Implement advanced machine learning algorithms, such as Transformer-based models, reinforcement learning, ensemble learning, and agent-based systems to continually improve the performance of our AI systems. Lead the processing and analysis of large, complex datasets (structured, semi-structured, and

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the Team Product Platform builds and owns the shared foundations the rest of Replit is built on, spanning the full stack so every other team can ship features safely and quickly. Identity & Authorization defines how people, agents, sandboxes, and services prove who they are and what they can do. These systems protect critical product and service interactions across Replit's web product, Agent, enterprise controls, and internal services. Our work is high-leverage and horizontal: when identity and policy are clear, reliable, and easy to adopt, every other team can move faster without rebuilding security controls. We are a small, collaborative team that values curiosity and clear thinking over pedigree, and we work in the open by bringing each other the problem rather than just the request. We care more about how you reason and build than the route you took to get here. About the Role As a Software Engineer , you will design, build, and operate the identity and authorization systems that protect critical interactions on Replit, including Agent acting on behalf of a user or holding their own identity. The work is guided by a few simple questions: Can every protected request prove which workload made it, which principal it represents, and who is acting on that principal's behalf? Can product teams express policy once and trust the same decision across web, mobile, Agent, and internal services? Can enterprise administrators control who can access each workspace, app, connector, and Agent capability without navigating a permission maze as well as having a legible ledger of decisions? Can Agent act for a user across long-running and durable work without receiving broad or long-lived credentials? Are identity and auth

About the Team API Frontiers turns OpenAI’s frontier models into production APIs that developers can use to build reliable products and agents. We own the core path connecting models to developers through the Responses API, with a focus on safety, reliability, and speed. Working closely with Research, Safety, Codex, and other API teams, we bring new model capabilities into production and improve them through developer feedback. About the Role We are looking for a backend software engineer to build and operate the services behind the Responses API. You will shape API behavior, bring new capabilities from research into production, and make long-running agent workflows dependable and fast. The work combines distributed systems engineering with product judgment: designing useful developer interfaces, managing staged rollouts, and following production issues through to durable fixes. In this role, you will: Design, build, and operate APIs and backend services that bring frontier model capabilities to developers. Partner with Research, Safety, Codex, and API teams to define API behavior and deliver safe, staged launches. Build API capabilities for agent workflows, including task delegation, context sharing, and parallel execution. Strengthen long-running request reliability across timeouts, cancellation, streaming, and background execution. Improve request-processing performance and tail latency through profiling, efficient systems code, and persistent connections. Turn developer feedback and production failures into better observability, diagnostics, and lasting product improvements. Your background might look something like: 5+ years of experience building and operating backend services or developer-facing APIs in production. Strong software engineering fundamentals, with practical knowledge of distributed systems, concurrency, and asynchronous execution. Ability to diagnose production failures and performance bottlenecks using observability data and profiling. Product

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 ship AI products. THE ROLE The largest, most demanding enterprises run on Baseten, and they bring exacting requirements for how people, services, and agents access the platform. This is the founding role for our identity and authorization team within enterprise engineering. You'll own the identity and access layer of the Baseten platform: the authorization model, credential systems, and admin experiences that enterprise IT teams use to govern access for organizations like Harvey, HubSpot, and Notion. You'll design and build Baseten's fine-grained authorization system from the ground up to support the workflows customers depend on today while giving them cleaner, more precise ways to manage access as the platform grows. Authorization at Baseten requires low-latency permission checks at high request volume, consistent contracts and behaviors across the product suite, and strong security guarantees for mission-critical, highly regulated workloads. EXAMPLE INITIATIVES Recent and upcoming work in this area: Fine-grained authorization for users, service accounts, and agentic workloads: per-resource permissions at the organization, team, and workload scope to support both common workflows and complex enterprise access policies Programmatic authentication allowing high-compliance customers to connect service principles securely via short-lived, workload-based credentials Agent credentials that grant an agent exactly the access it needs for the gi

As a Senior Software Engineer on Coder’s Agentic Engineering team, you’ll build and evolve the systems behind our agentic development experience. You’ll work across the agent harness, integrations, and workflows that connect agents with real development environments. You’ll stay hands-on, solve complex technical problems, and work closely with Product, Design, and other engineers to ship reliable agentic experiences. To provide substantive overlap with the team, this position must be in Eastern Time. What you’ll do here Design and build production systems in Go, with work across React and TypeScript where needed. Improve agent execution, tool use, context management, streaming, and long-running workflows. Extend our provider-agnostic architecture as models and capabilities change. Build reliable integrations between agents, workspaces, tools, and developer infrastructure. Own projects from implementation through rollout and iteration. Contribute to design reviews, code reviews, and technical discussions. Partner with Product and Design to turn agent capabilities into useful developer experiences. Improve the reliability, performance, and operability of agentic systems. What we’re looking for Strong experience building and operating production software systems. Hands-on experience with Go. Experience with React and TypeScript. Experience building systems around LLMs or agentic workflows. Familiarity with model APIs, tool calling, context management, or agent loops. Good understanding of distributed systems and production reliability. Working knowledge of AWS. Strong problem-solving skills and comfort working through technical ambiguity. Someone who contributes beyond their own code through reviews, collaboration, and knowledge sharing. Bonus tacos if you have Experience building coding agents, developer tools, or cloud development environments. Experience with MCP, agent tools, or multi-agent systems. Experience with remote execution, sandboxing, or isolated compute.

Salary range: $300k - $350k | Equity: 0.4% - 0.6% | In-Person: NYC About Datalab Datalab trains models that read documents reliably at scale. The world's most important information is trapped in PDFs, scans, and files that can't easily be parsed, and getting it out correctly matters. From frontier AI labs processing training data to Fortune 500s like Siemens extracting decades of engineering records, Datalab is where businesses turn to when extraction has to be right. We’re at an 8-figure run rate with a team of 7. Anthropic is a customer. And we have hundreds more across FAANG, frontier AI labs, healthcare, finance, government, and legal. Our tools, Chandra, Surya, Marker, and Lift, have 70,000+ GitHub stars and broad developer mindshare. We're backed by founding members of OpenAI, FAIR, and Hugging Face. Role Overview We're looking for an engineering lead to guide our team while staying hands-on in the code. You'll set the technical direction and standards for how we build the interfaces, tools, and infrastructure behind our OCR, extraction, and document-understanding systems. This includes everything from optimizing agent loops and interfaces to helping to speed up inference. This is a player-coach role. You'll manage and grow a team of three engineers, own engineering delivery and quality, and spend a large share of your time writing code - focused on architecture, infrastructure, and the hard problems rather than routine feature work. You’ll partner closely with the research team to define the handoff between experimentation and production. As a small and fast-moving team, roles are fluid and ownership is high. You'll work directly with the founder to set priorities, ship features, and make our technology accessible to a global community of builders. Day to day, you will: Manage and grow a team of three engineers - 1:1s, prioritization, feedback, and hiring as we scale. Own engineering delivery, quality, and technical standards across code, testing, infrastruct

At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 The Mission The Foundry is ClickUp's internal AI innovation lab — embedded inside GTM Systems and accountable for turning AI capabilities into production-grade, internally deployed products that make every GTM function faster and smarter. We build the infrastructure that powers AI-first work across Sales, Marketing, Post-Sales, and Revenue Operations. As the Senior Software Engineer on this team you will own the technical delivery of our MCP server platform, agent orchestration layer, and internal tooling — shipping production systems used daily by hundreds of ClickUp employees, and scaling your own throughput by treating AI tools as first-class engineering collaborators. What You'll Own MCP Server Platform Design, build, and operate Model Context Protocol servers that expose CRM, ticketing, analytics, and communication data to AI agents across the GTM stack Implement Okta PKCE authentication flows and RBAC policy enforcement so agents access only the data they're authorized to touch Maintain deployment infrastructure on AWS (Bedrock, Lambda, ECS, API Gateway) and contribute to GCP workloads where applicable Own observability: structured logging, distributed tracing, latency SLOs, and on-call runbooks for every production server Agent Orchestration & AI-Native Products Build and maintain multi-step autonomous agents that execute end-to-end GTM workflows — lead qualification, deal room assembly, onboarding automation, support triage, and more Architect prompt engineering frameworks, tool-call schemas, and agent evaluation harnesses that make AI behavior predictable and auditable Integrate with LLM p

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the role: We are seeking talented distributed systems engineers who are passionate about building innovative solutions for application deployment. Your mission will be to enhance the capabilities of Replit Infrastructure, optimize performance across global regions, and drive efficiency while delivering an exceptional user experience. If you have a strong foundation in software development, a deep understanding of cloud technologies, and a track record of delivering high-quality code, we want to hear from you. In this role you will: Expand Replit's cloud infrastructure offerings: Launch new cloud products to be used by Replit Agent to build complex apps. Collaborate with cross-functional teams to design and implement these features, empowering developers with a comprehensive suite of tools to build and deploy their applications efficiently. Enhance reliability and scalability: Identify bottlenecks, optimize critical paths, and implement robust monitoring and alerting systems. Work closely with the SRE team to ensure high availability and minimal downtime. Enable our customers to seamlessly scale their applications to meet the demands of their growing user base. Improve utilization of cloud infrastructure: Analyze our infrastructure costs and identify opportunities for optimization. Implement strategies to reduce cloud expenses without compromising performance or reliability. This could involve techniques such as resource provisioning, auto-scaling, cost-aware scheduling, and data lifecycle management. Your efforts will directly contribute to the financial efficiency of our cloud services. Required skills and experience: Distributed systems: Track record of working with platform-as-a-service, distributed storage, o

We are a global team of innovators and pioneers dedicated to shaping the future of observability. At New Relic, we build an intelligent platform that empowers companies to thrive in an AI-first world by giving them unparalleled insight into their complex systems. As we continue to expand our global footprint, we're looking for passionate people to join our mission. If you're ready to help the world's best companies optimize their digital applications, we invite you to explore a career with us! Do you get excited about complex distributed systems? Do you love data? We’re looking for an experienced technology leader to lead and grow our global engineering team and help our customers build better software by building the next generation of Application Performance Monitoring (APM) by leading our Agent teams. New Relic is committed to giving our customers valuable insights into their systems, and New Relic’s APM agents are used by tens of thousands of companies to evaluate and improve the performance of their most important business applications. Opportunity to work from a remote office may be available depending on the applicant's location. What you'll do Hands on with data analysis and technical problem solving Leverage open source tools like OpenTelemetry to acquire data Help design and build our APM agents that run in our customer environments and give engineers deep insight into application performance, and business line owners actionable intelligence on their business performance Build processes that ensure reliability, scalability, team growth and execution Work across teams to build engineering plans and execute, getting things done in a distributed, large-scale, and fast-growing environment This role requires 4+ years of experience leading people and teams 10+ years of experience in Software Engineering Proven track record of leading and scaling strong technical teams Experience handling high performing self-directed remote teams Capable of div

About the Team The Post-Training Frontiers team is responsible for training the frontier agents OpenAI ships to the world (GPT-Next). We train the flagship agentic models behind Codex, ChatGPT, and the API through large-scale reinforcement learning. The team’s work spans four areas. First, execution and science: working with teams across OpenAI to decide what can go into the final model and how, using scientific experiments and evals that are representative of the final pipeline so issues can be recognized early. Second, RL scaling: executing the final large-scale reinforcement learning run, making sure GPUs are used efficiently and training stays healthy. Third, research: improving horizontal capabilities like instruction following, factuality, memory, and multi-agent behavior, where the team’s broad visibility helps identify cross-cutting improvements across teams and domains. Fourth, engineering: maintaining the infrastructure stack and internal tools to ensure that both the final run and all integrations go as smoothly as possible and that the systems are easy to work with. About the Role This role focuses on keeping our frontier RL training runs fast, reliable, and unblocked. You will work across engineering and infrastructure problems as they emerge, from scaling and orchestration issues to inference bottlenecks, numerical problems, and hardware failures, as well as supporting large horizontal integrations in the big run, like multi-agent capabilities or memory. This is a role for a strong generalist who quickly learns anything needed for the task, has high attention to detail, debugs deeply, and is motivated by fixing the highest-impact problem in front of the team. In this role, you will: Keep large-scale async RL training runs moving by jumping into the most urgent engineering and infrastructure problems. Debug issues across training systems, inference, orchestration, scaling, and distributed infrastructure. Improve the reliability and efficiency of RL trai

About the Team The Platform Analytics team builds the systems OpenAI researchers use to understand the quality and behavior of the models we train including what models are doing, why they behave in a particular way, and how that behavior changes across experiments. Neptune is a core part of this work. It ingests, stores, queries, and visualizes large volumes of metrics from pretraining, post-training, and reinforcement learning. Hundreds of researchers depend on these systems in their daily work to compare experiments, debug unexpected behavior, and decide what to try next. Our scope is broader than metrics. We also build platforms that help researchers analyze samples, traces, evaluation results, and other structured or unstructured data through dashboards, APIs, and increasingly agent-driven workflows. These systems need to remain fast, reliable, and understandable as the scale and complexity of research change quickly. We are not trying to become a consulting team that builds a separate solution for every research project. We work directly with researchers to understand recurring problems, then turn them into reusable infrastructure and platform capabilities that many teams can build on. About the Role We’re looking for a hands-on experienced software engineer who can take ownership of a critical system and drive it from problem definition through production adoption. This person should be able to own a platform such as CacheHouse end to end: define its technical direction, design its data model and storage architecture, integrate it with several research dashboards and workflows, guide one or two engineers, and ensure the system works reliably for its users. The right candidate should already bring the technical judgment, ownership, and execution expected at this level. The primary learning curve should be OpenAI’s stack and research problem space, not learning how to lead a complex engineering effort or deliver a production system. You will work directly with

About the Team: Compute Infrastructure builds the platform that turns enormous amounts of compute into a reliable engine for frontier AI. We design, provision, schedule, operate, and optimize the systems that connect accelerators, CPUs, networks, storage, data centers, orchestration software, agent infrastructure, developer tools, and observability into one coherent experience for researchers and product teams. Our work spans the entire stack: capacity planning and cluster lifecycle, bare-metal automation, distributed systems, Kubernetes and scheduling, deep system optimization, high-performance networking, storage, fleet health, reliability, workload profiling, benchmarking, and the developer experience that lets teams use enormous compute systems with confidence. At this scale, small improvements to communication, scheduling, hardware efficiency, or debugging workflows can compound into meaningful research velocity. We are hiring across Compute Infrastructure rather than for a single narrow team, and we use this opening to match strong engineers to the problems where they can have the most leverage. About the Role We are looking for engineers who want to build the compute platform behind OpenAI's research and products. You may not be the strongest in low-level systems, high-performance computing, distributed infrastructure, reliability, CaaS, agent infrastructure, developer platforms, tooling, or the user experience around infrastructure. What matters is that you can reason carefully about complex systems, write durable software, and raise the quality and velocity of the people around you. Depending on your background and interests, you might work close to hardware, close to users, on CaaS and agent infrastructure, or on the control planes and data planes in between. You could help bring new supercomputing capacity online, optimize training workloads from profiler traces and benchmarks, improve NCCL and collective communication behavior, reason about GPUs, NICs, t

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. Snowflake is about empowering enterprises to achieve their full potential, and people too. With a culture that’s all in on impact, innovation, and collaboration, Snowflake is the sweet spot for building big, moving fast, and taking technology, and careers, to the next level. About the Role The Cortex Code team is building the future of coding agents for working with data. See our flagship product in action: Cortex Code in Action: Live Demos + AMA . Your work will directly impact how developers and businesses build with data. You'll own the full AI engineering lifecycle: design, prompt/tool engineering, evals, deployment, measurement, and optimization. You'll work with a small, high-powered modeling and infrastructure team. What you will do in this role: Own features end-to-end for Snowflake Cortex Code products. Build agentic workflows, coding harnesses, evaluation pipelines. Build enterprise-grade context engineering: function calling, tool schemas, guardrails, agent teams, and verification/repair. Partner with product and infra: translate customer problems into products and experiments. Collaborate with infrastructure teams to productionize improvements. Work with an elite team of engineers towards building great products Requirements: Bachelor’s degree in Computer Scienc

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 Identity & Access management (IAM) team’s charter is to enable our customers to confidently bring their most sensitive data and workloads to Snowflake. We provides the authentication and authorization capabilities for customers to secure their Snowflake accounts. We are heavily focused on critical AI adoption and security capabilities like Snowflake Intelligence access control, MCP server and clients, Agent identity, Admin guardrails for agents etc. Our feature set includes capabilities like user management, secret-less authentication for both human and service users, SSO integration with numerous IdPs, MFA, OAuth and OIDC support for 3P applications, and RBAC for granular access control. Our systems are critical to customer trust and maintaining Snowflake’s security, reliability and performance. The team culture is very collaborative with ample opportunities for growth and mentorship from Principal engineers. AS A SENIOR SOFTWARE ENGINEER - IDENTITY & ACCESS MANAGEMENT, YOU WILL: Design and implement critical AI security capabilities for controlled, audited, restricted agent workflows, both inbound and outbound. Design and implement features that provide critical identity and access management capabilities, including integration with the next generation identit