Infrastructure Security Engineer in United States

About the Team OpenAI, in close collaboration with our capital partners, is embarking on a journey to build the world’s most advanced AI infrastructure ecosystem. The Stargate team is central to this mission, setting the core infra strategy and implementing this vision. From site selection to the buildout process, this team sits at the intersection of commercial, technical, strategy, and operations, interacting with teams and executives inside and outside of OpenAI. About the Role The New Geography and International Growth Lead will own the strategy for infrastructure expansion into new geographies, including market assessment, stakeholder engagement, and coordination across energy, policy, commercial, and other infrastructure workstreams. This role identifies and enables priority international growth opportunities while ensuring alignment with regional regulatory, operational, sustainability, and long-term infrastructure objectives. This is an individual contributor lead role and does not have direct reports initially. The role will translate ambiguous market-entry questions into clear recommendations, identify the conditions required for OpenAI to advance in new regions, and coordinate the cross-functional work needed to turn priority geographies into executable infrastructure options. Key Responsibilities Build market-entry frameworks for international infrastructure geographies, including power availability, land readiness, regulatory posture, commercial fit, and execution risk. Assess priority regions and countries against OpenAI’s long-term compute, energy, sustainability, policy, and operational objectives. Coordinate cross-functional geographic diligence with energy, policy, commercial, legal, finance, procurement, engineering, and site-readiness stakeholders. Lead early stakeholder mapping and engagement strategy with utilities, regulators, government entities, developers, capital partners, and other market participants. Translate regional findings into exe

About the Team OpenAI, in close collaboration with our capital partners, is embarking on a journey to build the world’s most advanced AI infrastructure ecosystem. The Industrial Compute team is central to this mission, setting the core infra strategy and implementing this vision. From site selection to the buildout process, this team sits at the intersection of commercial, technical, strategy, and operations, interacting with teams and executives inside and outside of OpenAI. About the Role Responsible for validating that proposed sites are buildable, compliant, and cost-effective. You will lead diligence across civil, geotechnical, environmental, and entitlement dimensions, identifying risks and driving mitigation strategies. Key Responsibilities Lead all technical diligence: geotech, soils, title/ALTA surveys, mineral rights, and access. Oversee permitting/entitlement path and schedule governance with agencies. Evaluate generator air permits, wetlands, floodplain, and stormwater constraints. Manage consultants performing feasibility studies and environmental assessments. Deliver go/no-go recommendations with risk and mitigation options. Build diligence templates and playbooks to scale future site reviews. Qualifications 8+ years in land development, civil/environmental engineering, or data center diligence. Knowledge of permitting, entitlements, and AHJ engagement. Strong project management and technical review skills. Experience managing consultants and interpreting complex studies. Regularly communicate site readiness updates, risks, and milestones to executive stakeholders Establish and track key performance indicators to assess the effectiveness of the site selection program and the contributions of external vendors and partners. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely depl

About the Team OpenAI, in close collaboration with our capital partners, is building the world’s most advanced AI infrastructure ecosystem. The Site Readiness & Development team owns the upstream diligence and development work required to convert powered-land opportunities into executable infrastructure options. About the Role The Power Land Developer; Development & Power Projects will support the advancement of powered-land opportunities across the portfolio, reporting to the Development & Power Project Lead. This is an individual contributor lead role and does not have direct reports initially. This role will own day-to-day development execution across approximately 1–3 active sites depending on complexity, including utility applications, interconnection requests, study follow-through, queue milestones, consultant workstreams, schedule and risk management, and readiness handoff for opportunities advancing to deeper diligence, commercial commitment, or execution. The role translates study and utility findings into clear schedule, budget, and risk implications for portfolio decisions. Responsibilities Manage day-to-day advancement of powered-land opportunities from intake through readiness. Own utility application and interconnection follow-through across active powered-land opportunities, including utility inputs, study responses, and queue milestones. Scope and manage external studies and consultant workstreams needed to validate readiness. Track development schedules, dependencies, risk registers, site-readiness milestones, and key budget implications. Translate technical findings into clear schedule, budget, and risk implications and escalate material blockers or trade-offs to the Development & Power Project Lead. Partner with land, environmental, economic development, and community affairs leads to align project advancement. Support expansion planning, infrastructure sequencing, and long-term power-risk mitigation. Define readiness criteria and

About the Team The Applied AI team safely brings OpenAI's technology to the world. We released ChatGPT, Plugins, DALL·E, and the APIs for GPT-4, GPT-3, embeddings, and fine-tuning. We also operate inference infrastructure at scale. There's a lot more on the immediate horizon. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. We serve end-users directly through ChatGPT, and serve developers through our APIs, which power product features that were never before possible. About the Role The Engineering Acceleration team designs, builds and maintains the foundational systems that engineers use to build ChatGPT and the API. This is a fast-growing team and you will get a chance to own and define the strategy, vision, and plan for how to increase developer productivity. In this role, you will: Drive the design, development, and implementation of tools, systems, and processes that accelerate engineering velocity, reduce manual effort, and increase the quality of output. Use our latest AI tools to re-think how we can be the most productive team in the industry. Work closely with various teams within OpenAI to understand their workflows, challenges, and needs, and ensure the tools and systems built by the Engineering Acceleration team address these requirements. Bring new features and research capabilities to the world by partnering with product engineers to lay the necessary technical foundations. Guide and advise product engineering teams on best practices for ensuring observable, scalable systems. Like all other teams, we are responsible for the reliability of the systems we build. This includes an on-call rotation to respond to critical incidents as needed. You might thrive in this role if you: Have 5+ years of experience in engineering, including 3+ years of experience in infrastructure building tooling for developers. Have experi

About the Team OpenAI, in close collaboration with our capital partners, is embarking on a journey to build the world’s most advanced AI infrastructure ecosystem. The Industrial Compute team is central to this mission, setting the core infra strategy and implementing this vision. From site selection to the buildout process, this team sits at the intersection of commercial, technical, strategy, and operations, interacting with teams and executives inside and outside of OpenAI. About the Role The Clean Energy and New Technology Lead will own infrastructure clean energy and emerging energy technology strategy and execution, identifying and deploying scalable solutions that enable resilient, low-carbon compute and data center growth. The role will work closely with regulatory and policy teams to align infrastructure expansion with OpenAI’s long-term environmental and operational objectives. This is an individual contributor lead role and does not have direct reports initially. The role will evaluate where emerging energy technologies can materially improve reliability, cost, carbon, speed, or resilience; translate those options into practical deployment pathways; and help ensure OpenAI’s infrastructure growth remains aligned with sustainability considerations. Key Responsibilities Evaluate emerging energy solutions such as clean firm power, advanced storage, grid flexibility, low-carbon backup power, heat reuse, water-related energy efficiency, and other scalable technologies where relevant. Identify pilot opportunities and deployment pathways that can move promising energy technologies from concept to commercially and operationally credible execution. Translate technical options into clear reliability, cost, schedule, carbon, regulatory, and operational implications for infrastructure decision-making. Partner with energy regulatory, policy, procurement, engineering, deployment, finance, legal, and site-readiness teams to align technology and sustainability choices with

About the Team Training Runtime builds the distributed systems that power OpenAI's largest model training runs - most recently GPT-5.5! The Data Movement area owns the infrastructure that keeps training jobs supplied with the right data at the right time, and keeps model state moving safely and efficiently across large clusters. Our work spans machine learning systems, distributed storage, high-throughput data loading, reliability engineering, and developer experience. Success means researchers can move quickly while training runs remain fast, reproducible, debuggable, and resilient at scale. About the Role We are looking for a deeply hands-on Technical Lead Manager to own datasets throughout our training infrastructure. This person will set the direction for how training jobs read data: the APIs, storage contracts, versioning model, benchmarks, debugging tools, and reliability guarantees that make data access consistent across current and future training frameworks. You will begin as the primary technical owner for dataset reads, working directly in the code while aligning researchers, training framework owners, storage teams, and infrastructure partners around a durable platform. The problem is deceptively hard at frontier scale: make enormous, heterogeneous datasets easy to consume, correct across distributed workers, observable when something goes wrong, and flexible enough to support pretraining, reinforcement learning, and multimodal training. In this role, you will Design and build a unified dataset read platform for multiple current and future training frameworks. Define dataset APIs, storage-format expectations, registration/versioning, and migration paths that make data access reproducible and maintainable. Build reliability into the read path, including stateful iteration, caching, fast restart, recovery, and clear operational contracts. Build terminal and web-based visualizers that let teams inspect text, multimodal, and reinforcement learning data late

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 OpenAI, in close collaboration with our capital partners, is embarking on a journey to build the world’s most advanced AI infrastructure ecosystem. The Industrial Compute team is central to this mission, setting the core infra strategy and implementing this vision. From site selection to the buildout process, this team sits at the intersection of commercial, technical, strategy, and operations, interacting with teams and executives inside and outside of OpenAI. About the Role The Community Engagement Lead will serve as the primary liaison between OpenAI and the communities where it plans to develop data centers, including Effingham County and the greater Savannah Metropolitan Area. This role ensures that OpenAI builds strong, trust-based relationships with local stakeholders, communicates proactively about our projects, and integrates community priorities into our development approach. The role spans engagement, communications, and reputation management, and will partner closely with the Economic Development and Environmental leads. Key Responsibilities Build and maintain relationships with local leaders, community organizations, NGOs, and residents. Develop and execute community engagement strategies for new and existing sites. Represent OpenAI in public forums, hearings, and community events. Partner with the Economic Development Lead on incentive compliance and community benefits. Partner with the Environmental Lead on communicating environmental stewardship and sustainability efforts. Develop proactive communications to address concerns, highlight benefits, and reduce risk of opposition. Monitor community sentiment and advise executives on risks and opportunities. Create a community engagement playbook that can scale across geographies. Qualifications 8+ years in community affairs, public engagement, or corporate communications. Proven track record engaging diverse community stakeholders for large infrastructure or technology projects. Strong publ

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 OpenAI, in close collaboration with our capital partners, is embarking on a journey to build the world’s most advanced AI infrastructure ecosystem. This team is central to this mission, setting the core infra strategy and implementing this vision. From site selection to the buildout process, this team sits at the intersection of commercial, technical, strategy, and operations, interacting with teams and executives inside and outside of OpenAI. About the Role We are seeking experienced Data Center Mechanical and Electrical/Power Design Engineers with expertise in designing, operating, and maintaining large-scale data center campuses. The ideal candidate for this role will have extensive background and experience in design and managing critical equipment and facilities, design and operation of MEP (Mechanical, Electrical, Plumbing) systems, and overseeing operational activities from initial phases of Data Center build through delivery and ongoing maintenance. The ideal candidate will have a strong technical background, operational leadership experience, and a proven ability to collaborate with external vendors on critical infrastructure. This role offers the opportunity to lead transformative data center projects with high visibility and impact. If you are passionate about delivering cutting-edge infrastructure solutions, we encourage you to apply. Key Responsibilities Oversee building and MEP design, operation, and maintenance, including reviewing building and MEP drawings and proposals across all project phases. Lead operational activities for large-scale data center campuses, from early design phases through delivery and daily operation. Operate and maintain critical data center facilities and equipment, ensuring reliability and performance. Collaborate with external vendors to select, procure, and manage critical equipment, such as generators, UPS, chillers, and CDUs. Provide technical expertise on all aspects of data center building, equipment, 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

About the Team OpenAI, in close collaboration with our capital partners, is embarking on a journey to build the world’s most advanced AI infrastructure ecosystem. The Infrastructure team is central to this mission, setting the core strategy and implementing the vision. From site selection to deployment to operations, this team sits at the intersection of commercial, technical, and operational domains, interacting with experts and executives inside and outside of OpenAI. We design and operate mission-critical facilities that support cutting-edge AI workloads at scale. About the Role We are seeking a Facilities Operations Lead to support the commissioning, deployment, and long-term operation of our next-generation AI data centers. This role bridges the interface between data center construction and hardware landing, ensuring seamless integration of mission-critical infrastructure with hardware deployment timelines. You will define and execute commissioning plans, support infrastructure bring-up, and take ownership of operations and maintenance for cutting-edge, large-scale, AI data centers. You will collaborate closely with design, construction, and hardware teams to define repeatable processes for new data center builds and lead hands-on operations to uphold the performance and reliability of our deployed infrastructure. Key Responsibilities Define and execute sequences of operations, commissioning steps, and bring-up processes for mission-critical data center facilities. Interface with the design and hardware teams to define deployment procedures tailored to each data center and hardware configuration. Oversee installation, commissioning, and operational readiness of large-scale data center campuses. Manage monitoring, maintenance, and quality control of the data center infrastructure, including high-performance liquid cooling systems. Develop on-site operations staffing strategy. Develop and enforce procedures for planed and unplanned downtime and SLAs for critical

About the Team OpenAI’s Financial Engineering (FinEng) team powers how revenue flows through our products—pricing & packaging, checkout, payments, subscriptions, and the financial infrastructure behind them. We partner with Product, Engineering, Risk, Finance, and Go-to-Market to make paying for OpenAI products seamless, reliable, and efficient worldwide. About the Role As a Data Scientist on FinEng, you’ll own the analytics and experimentation that improve our checkout and payments , subscriptions , and pricing & monetization systems. You’ll define the metrics that matter, build the source-of-truth data assets, and design experiments that increase conversion, reduce churn and payment failures, and expand global payment method coverage. Your work will directly influence revenue, customer experience, and how we scale internationally. 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 Own checkout & payments analytics and experimentation across methods and locales (e.g., bank transfers, emerging rails), improving conversion while monitoring risk and latency. Build and run the experimentation program for in-house checkout—define success metrics and guardrails, execute staged rollouts, and use offline incrementality when online tests aren’t feasible. Create operational visibility and source-of-truth data with FinEng Data Engineering—land team-level metrics, SLAs, and self-serve dashboards that drive proactive action. Lead subscription, retention, and monetization analytics—ship launch-readiness for new subscription features, reduce involuntary churn (e.g., targeted retrials/nudges), and develop elasticity/FX frameworks toward pricing optimality. You might thrive in this role if you have 5+ years in a quantitative role (data science, product analytics, or experimentation) in high-growth or fintech environments Fluency in SQL and Python ,

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: OpenAI, in close collaboration with our capital partners, is embarking on a journey to build the world’s most advanced AI infrastructure ecosystem. Our Stargate program develops and deploys massive, state-of-the-art data center campuses in partnership with industry leaders today—and through future OpenAI infrastructure projects tomorrow. We design for scale, speed, and reliability, and we need experienced technicians who can translate network blueprints into physical reality. About the Role: We are seeking a Senior Data Center Networking Technician who thrives in fast-moving build environments and is eager to roll up their sleeves during active datacenter deployments. Your first assignment will focus on the physical bring-up of network infrastructure at a large partner-operated campus, collaborating with partner teams and their delivery vendors to achieve agreed performance and reliability targets. As that campus reaches steady state, you will transition to lead network deployment for future OpenAI data center projects, defining standards and guiding implementation across multiple locations. Candidates must be able to sit onsite in Abilene, Texas 5 days per week Key Responsibilities Serve as OpenAI’s technical lead technician during the current campus build, partnering with internal engineers and external contractors on design reviews, installation plans, and acceptance criteria. Spend significant time on the data-center floor performing inspections, assisting with cable routing/termination when needed, conducting fiber testing (OTDR, power levels, continuity), and resolving installation challenges in real time. Troubleshoot and optimize cabling routes, patching, and equipment turn-up to ensure clean, reliable handoff to network operations. Contribute to design discussions and peer reviews for structured cabling and physical network layouts, providing practical field feedback to engineering teams. Develop repeatable engineering standards, as-built do