Infrastructure Engineer in United States

About the Team The Private Computing team works across product, engineering, security, and safety to build advanced privacy products and infrastructure at OpenAI. Our mission is to provide world-class security features to users so their private data remains private, even from OpenAI. We use technologies like confidential computing, trusted execution environments, and end-to-end encryption to ship product features across ChatGPT, the API, and our future consumer devices. About the Role We’re looking for software engineers to design, build, and scale novel privacy features and infrastructure across ChatGPT, API, and future consumer devices. In this role, you will: Ship fast while balancing difficult trade-offs in complex domains Build core abstractions for trusted execution environments and end-to-end-encryption Build product features for private inference and storage across ChatGPT, API, and future consumer devices Update build systems to increase trust and verifiability Integrate with safety and integrity infrastructure Operate systems at scale with high reliability, including an on-call rotation Collaborate with a diverse set of cross-functional teams across product, engineering, security, safety, policy, and legal You might thrive in this role if you: Care deeply about user privacy and security Have 5+ years of experience in professional software engineering Have experience building and scaling confidential computing or encryption technologies in production environments Have experience with Kubernetes and cloud orchestration systems Take pride in building and operating scalable, reliable, secure systems Can collaborate well and drive alignment in the face of difficult trade-offs Are comfortable with ambiguity and rapid change Workplace & Location This role is based in San Francisco, CA. We follow a hybrid model with 4 days a week in the office and offer relocation assistance to new employees. About OpenAI OpenAI is an AI research and deployment company dedicat

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 Monetization team is a new cross-functional group working across engineering, product, research, and design to build the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to develop user-first, privacy-preserving monetization products, including next-generation ads experiences, that strengthen user trust, unlock economic opportunity, and support OpenAI’s long-term innovation. Monetization plays a critical role in enabling OpenAI to continue pushing the boundaries of AI capabilities while ensuring the benefits of AGI are broadly shared. We believe monetization must be aligned with user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem of developers, advertisers, and businesses. This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, and Research to bring new ad experiences into real-world systems across OpenAI surfaces at global scale, including thoughtfully integrating them into the core ChatGPT experience. About the Role We’re looking for an experienced Software Engineer to help build the creative rendering and presentation layer of OpenAI’s ads ecosystem. This is a foundational role responsible for defining how ads are structured, rendered, and delivered across different surfaces, platforms, and media types. You’ll work across the full technical stack to build infrastructure and tooling for new ad formats, including text, image, video, native, conversational, and interactive experiences. You will help ensure these formats render reliably, perform efficiently, and feel natural within the core ChatGPT experience. You’ll collaborate deeply with Product, Design, and Research to create ads experiences that are useful, high-quality, privacy-preserving, and aligned with OpenAI’s standards for safety and user trust. In this role, you will: Design, build, and

About the Team Frontier Systems Foundations, part of Compute Foundations at OpenAI, builds the systems software foundation that turns new compute infrastructure into reliable, usable capacity for frontier model training. Our mission is to make some of the world's largest GPU clusters work reliably for frontier training. We bring new platforms and clusters online, safely maintain installed fleets, and partner with hardware, infrastructure, and research teams to resolve the system-level issues that keep jobs from running. That means building and maintaining the software closest to the machine: Linux and Ubuntu operating-system images, kernels and modules, drivers, packages and repositories, disks and boot configuration, firmware integration, provisioning, and system-level validation. We make these components reproducible, compatible, and safe to operate across heterogeneous fleets. About the Role We are looking for systems software engineers with deep Linux and host-systems experience to build, qualify, and maintain the operating-system foundation for OpenAI's frontier compute fleet. Relevant backgrounds include kernel and module development, Linux distribution or image engineering, package management, firmware and driver integration, disks and boot, and bare-metal provisioning. You'll work closely with hardware engineers, vendors, and infrastructure teams to bring up new platforms, integrate system components, and debug failures across firmware, disks, boot, operating systems, kernels, drivers, and workload interactions. Your work will directly influence how quickly new capacity becomes usable and how reliably large GPU fleets operate. You should be comfortable writing and maintaining production-quality systems software and automation, but we do not expect expertise across every layer. This is an opportunity to go deep on challenging systems problems while building the image, package, qualification, and recovery paths that power the next generation of frontier models

We’re looking for a Software Engineer to architect and build backend systems that enforce data privacy and automate compliance at scale. You’ll work closely with product, infrastructure, security, and legal teams to embed privacy-by-design into our data and access layers. This is a hands-on, high-impact role for an experienced engineer who is passionate about protecting user data while enabling innovation. What You’ll Do Design, build, and operate backend services that enforce policy-driven data access, lifecycle controls, and privacy protections. Develop distributed authorization and identity-aware enforcement mechanisms integrated directly into data services and control planes. Implement auditability, policy hooks, and enforcement observability to ensure compliance is continuously verifiable. Partner with Security, Legal, and Compliance to convert privacy requirements into scalable technical designs and developer-friendly APIs. Harden data platforms and backend services through schema-level controls and data handling constraints by default. Collaborate with infrastructure teams to ensure consistent enforcement across systems while minimizing duplicated implementations. Contribute patterns, libraries, and education that elevate trustworthy data access patterns across the organization. You Might Thrive in This Role If You Have 5+ years of industry experience building and operating backend or infrastructure systems in production. Strong software engineering fundamentals , with fluency in at least one major programming language (e.g., Python, Go, Rust, C++, Java). Experience with distributed authorization, RBAC/ACL systems, encryption-based access, or policy engines. Familiarity with global privacy regulations and their architectural implications. Ability to influence and collaborate with teams across legal, compliance, product, and engineering. A bias toward practical, impactful solutions that balance privacy protections with product needs. Nice to Have Experience wi

About the Team The Core Services team is responsible for building and managing foundational services. It acts as the bridge between core infrastructure (e.g. compute, storage, networking) and product engineering teams, and enables product teams to move fast, build reliably, and scale efficiently. About the Role As a software engineer in the core services team, you will design and operate critical backend platforms such as caching systems, workflow orchestration, metadata stores, and file services. You’ll focus on building highly reliable, scalable, and performant systems that serve as the backbone of our products. We’re looking for people who are passionate about building infrastructure that empowers product teams, love working on distributed systems challenges, and enjoy creating well-designed APIs and abstractions that accelerate development. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design, build, and maintain shared infrastructure services such as caching layers, workflow orchestration (Temporal), metadata stores, and file storage services. Collaborate with product teams to provide scalable, reliable primitives that abstract the complexities of distributed systems. Improve performance, resilience, and scalability of core services that power customer-facing applications. You might thrive in this role if you: Have experience with distributed systems, caching infrastructure (e.g., Redis, Memcached), metadata storage (e.g., FoundationDB), or workflow orchestration (e.g., Temporal, Cadence). Have experience running containerized services in cloud environments and integrating them into automated build/test/release (CI/CD) workflows. Understand trade-offs in consistency models, replication strategies, and performance optimization in multi-region systems. Excel at communication and collaboration with cross-functional teams, and are obsesse

About the Team We are building general-purpose robotics. In the short term, we are focused on robots to support skilled workers to build our future infrastructure. In the long term, we imagine everyone having a personal robot doing anything they need. Progress is rapid, and based on a foundation of co-design between robotics hardware and ML research. About the Role As a Firmware Engineer, you will define and drive the architecture of embedded systems for next-generation hardware products. You will own foundational firmware decisions across real-time execution, device bring-up, hardware interfaces, fault handling, safety mechanisms, and production readiness. We’re looking for someone with deep experience building safety-critical or high-consequence systems, where failures can have meaningful consequences. You should be comfortable reasoning about risk, designing for diagnosability and graceful degradation, and creating engineering practices that raise the reliability bar for the entire team. You should also be unusually good at moving fast. Sometimes the right answer is a carefully reviewed architecture that will endure for years; sometimes it is getting a rough-but-useful prototype working by the end of the afternoon so the team can learn something concrete tomorrow. We value engineers who know the difference, make that call well, and can operate credibly in both modes. You will be both a technical leader and a hands-on builder: setting direction, reviewing critical designs, unblocking the hardest problems, and writing production firmware when it matters most. Our embedded stack uses a lot of Rust. Extensive experience in the language is a big help! This role is based in San Francisco, CA. This role will be expected to be in office 4 days per week and offer relocation assistance to new employees. In this role, you will: Rapidly bring up new hardware and set execution pace for the team. Lead firmware architecture for embedded systems spanning boot, RTOS/runtime behav

About the Role The Engineering Acceleration team builds and operates the foundational systems that engineers use to build, test, and ship ChatGPT, the API, and OpenAI's infrastructure. We are looking for an engineer to help evolve OpenAI's build and continuous integration systems for a fast-growing engineering organization. This role sits at the intersection of developer productivity, build systems, distributed infrastructure, and software quality. You will work on the systems that determine how quickly and confidently engineers can move: Bazel-based builds, Buildkite pipelines, test selection, remote caching and execution, CI observability, and tooling that helps engineers understand and fix failures quickly. Our mission is to make OpenAI one of the most productive engineering organizations in the world while preserving a high bar for correctness, reliability, and safety. The best version of this work is invisible when it succeeds: builds are fast, tests are trusted, CI failures are understandable, and engineers can focus on shipping useful systems instead of fighting infrastructure. In This Role, You Will Own and evolve Bazel-based build and test workflows across a large, polyglot monorepo. Design and maintain Starlark rules, macros, toolchains, and integrations that make builds reproducible, hermetic, and easy for product teams to adopt. Improve CI performance and reliability across Buildkite pipelines, including queue time, build time, cache hit rates, test sharding, retry behavior, and flake isolation. Build systems that reduce unnecessary CI work through affected-target detection, dependency graph analysis, test selection, caching, batching, and smarter scheduling. Improve local development workflows so engineers can reproduce CI behavior, debug build failures, and iterate quickly without learning every detail of the build stack. Operate and optimize build infrastructure across Docker/OCI images, Kubernetes-based runners, cloud resources, and remote cache/exec

About the Team The Platform Systems team at OpenAI operates at the intersection of cutting-edge AI and large-scale distributed systems. We build the engineering and research infrastructure required to train OpenAI’s flagship models on some of the world’s largest, custom-built supercomputers. Our team develops core model training software and works deep in the stack - spanning collective communication, compute efficiency, parallelism strategies, fault tolerance, failure detection, and observability. The systems we build are foundational to OpenAI’s research velocity, enabling reliable, efficient training at frontier scale. We collaborate closely with researchers across the organization, continuously incorporating learnings from across OpenAI into the evolution of our training platform. About the Role As a Software Engineer, Platform Systems, you will design and build distributed systems that provide visibility into large-scale training workloads and help operate them reliably at scale. You’ll work on failure detection, tracing, and observability systems that identify slow or faulty nodes, surface performance bottlenecks, and help engineers understand and optimize massive distributed training jobs. This infrastructure is critical to operating OpenAI’s training stack and is actively evolving to support new use cases and increasingly complex workloads. This role sits at the core of our training infrastructure, blending systems engineering, performance analysis, and large-scale debugging. In This Role, You Will Design and build distributed failure detection, tracing, and profiling systems for large-scale AI training jobs Develop tooling to identify slow, faulty, or misbehaving nodes and provide actionable visibility into system behavior Improve observability, reliability, and performance across OpenAI’s training platform Debug and resolve issues in complex, high-throughput distributed systems Collaborate with systems, infrastructure, and research teams to evolve platform

About the Team We’re hiring software engineers to make OpenAI’s Model Performance teams more productive. These teams work on the systems, tooling, and infrastructure that help improve model performance across OpenAI’s training and inference workloads at frontier scale. About the Role We’re looking for an autonomous, high-ownership developer productivity engineer who cares deeply about helping other engineers move faster, safer, and with more confidence. This role will sit within OpenAI’s Model Performance organization, contributing to developer infrastructure, CI systems, testing workflows, tooling, and broader performance infrastructure efforts. There is also a strong opportunity to contribute to the Triton project and help improve the systems that support performance-critical engineering work across OpenAI. In this role you will: Improve development workflows for engineers working on model performance infrastructure Design and improve CI/CD, release, validation, and testing pipelines Build and maintain tools that improve reliability, iteration speed, and engineering confidence Partner closely with engineers to identify friction in testing, debugging, deployment, and development workflows Contribute to infrastructure efforts that support performance-critical training and inference systems Help improve developer experience across Python-heavy codebases and performance-oriented infrastructure Work in a high-context, ambiguous environment where ownership and good judgment matter You might thrive in this role if: You are motivated by enabling the people around you and helping engineers do their best work You have strong experience with CI/CD, developer infrastructure, testing systems, tooling, or build/release workflows You are highly collaborative, empathetic, and comfortable partnering deeply with technical teams You are strong in Python and enjoy building reliable, scalable developer tools and infrastructure You have experience improving large-scale engineering work

About the Team We’re hiring software engineers to make OpenAI’s networking teams more productive. These teams build and operate the high-performance networking systems that support OpenAI’s training and inference infrastructure at frontier scale. About the Role We’re looking for someone who cares deeply about the developer experience of engineers working on complex infrastructure systems — especially around build systems, test architecture, release pipelines, and reliable development workflows. This role will be embedded with OpenAI’s networking team: making it faster, safer, and easier for engineers to build, test, validate, and ship changes across multi-server, networked, and hardware-adjacent environments. In this role you will: Improve development workflows for engineers building and operating OpenAI’s networking systems Design and improve continuous deployment, release, and validation pipelines Build and maintain test harnesses for multi-server, networked, and hardware-backed environments Improve iteration speed across C++, Python, and build-system-heavy codebases Partner with engineers to identify friction in CI, testing, debugging, and deployment workflows Drive testing and reliability strategy for infrastructure components that support large-scale training and inference workloads Work closely with centralized developer experience teams while staying deeply embedded with the networking engineers closest to the systems You might thrive in this role if: You are motivated by helping other engineers move faster and with more confidence You have experience with CI/CD, release pipelines, testing infrastructure, or build systems You are comfortable moving between C++, Python, and build systems such as CMake, Bazel, or Blaze You enjoy building test harnesses, automation, and workflow improvements for complex systems You do not need to be a networking expert, but you are excited to learn enough about the domain to make the team meaningfully more effective When you see

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. Senior Software Engineer — Cortex Training The Snowflake ML Platform team's mission is to let customers run their most demanding ML/AI workloads inside Snowflake. Cortex Training is our LLM post-training platform: it turns scarce, expensive GPU capacity into a simple, composable service, so customers can adapt open-weight foundation models to their own business problems while we handle the hard distributed-systems parts, including scheduling, orchestration, multi-node training and inference, fault tolerance, and throughput. The platform already runs post-training at scale. Under the hood, it decouples GPU computation from the training loop and exposes it as primitive APIs that compose into everything from SFT to full RL workflows. You'll work alongside a team that ships fast & sweats reliability and the researchers behind DeepSpeed. We're looking for an engineer who thrives in the ML infrastructure layer and brings a solid understanding of LLMs and post-training to help us scale and grow it. YOU WILL: Design and build across the full stack — from the public training APIs and SDK through the control plane to the GPU data plane. Scale the distributed systems that make GPU compute serverless — multi-tenant scheduling, placement, and capacity-aware routing across regional G

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. Company Overview We are building the next generation of cloud security infrastructure, focusing on advanced Data Exfiltration Protection (DXP) and unified Data Movement Policies (DMP). Our mission is to provide seamless, context-aware security that protects sensitive data without hindering developer velocity. We are looking for a visionary Principal Engineer to lead the technical strategy and architecture for our Data Movement and Perimeter control systems. Role Summary As a Principal Engineer in the Data Protection group, you will be the technical lead for the Data Exfiltration Protection (DXP) and Data Movement Policy (DMP) initiatives. You will bridge the gap between high-level security policy and low-level system enforcement, ensuring that our perimeter controls are robust, scalable, and deeply integrated with context-aware access policy frameworks. You will be responsible for the architectural evolution of our egress control systems, moving from simple IP-based rules to sophisticated, content-aware, and identity-driven data movement governance. AS A PRINCIPAL SOFTWARE ENGINEER - IDENTITY, DATA SECURITY AND TRUST AT SNOWFLAKE YOU WILL: Architectural Leadership: Lead the design and implementation of the Data Movement Policy (DMP) framework, ensuring it can handle complex

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. As a Chemical and Slurry Systems Engineer within Micron’s Global Facilities and Construction Team, you will deliver engineering expertise supporting the planning, design, construction, operation, and maintenance of facilities systems across Micron’s global manufacturing network. You will participate in capacity and scenario planning, evaluate impact to facilities infrastructure, and serve as a technical domain expert throughout all project phases. Your work ensures environmental, safety, regulatory, and code compliance while driving system reliability and operational excellence. Responsibilities Develop safe, reliable designs for Chemical and Slurry systems and ensure compatibility of materials of construction with all chemicals used. Create, review, and maintain corporate equipment specifications, engineering standards, and design guidelines. Advise sites on system capacity, load projections, and scenario‑driven impacts. Provide technical feedback on infrastructure additions or modifications to support manufacturing and technology roadmap changes. Supply Micron standards to design partners and conduct timely reviews of design packages, construction documents, and engineering work. Support project cost and schedule development and validate scope alignment with collaborator requirements. Coordinate with Facilities, Design, Construction, Procurement, and Manufacturing to ensure clear communication and project alignment. Provide technical guidance during construction,

This is where your work makes a difference. At Baxter, we believe every person—regardless of who they are or where they are from—deserves a chance to live a healthy life. It was our founding belief in 1931 and continues to be our guiding principle. We are redefining healthcare delivery to make a greater impact today, tomorrow, and beyond. Our Baxter colleagues are united by our Mission to Save and Sustain Lives. Together, our community is driven by a culture of courage, trust, and collaboration. Every individual is empowered to take ownership and make a meaningful impact. We strive for efficient and effective operations, and we hold each other accountable for delivering exceptional results. Here, you will find more than just a job—you will find purpose and pride. Your Role at Baxter As a Principal DevOps Engineer, you will provide technical leadership in the design, implementation, deployment, and support of cloud and platform engineering solutions that enable product development teams. You will partner across engineering functions to build scalable, reliable, and secure infrastructure while helping drive operational excellence through automation, observability, and continuous improvement. What You'll Do: Design, implement, and support cloud infrastructure solutions that enable the development and operation of Baxter products and applications. Manage infrastructure, platform, and deployment processes for product teams to ensure reliability, scalability, and performance. Deploy, manage, and troubleshoot containerized applications using Kubernetes and cloud-native technologies. Develop and maintain Infrastructure as Code (IaC) solutions using Terraform to automate infrastructure provisioning and management. Implement and support observability, monitoring, and alert