Infrastructure Security Engineer in United States

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . Pinterest brings millions of people the inspiration to create a life they love. Behind that experience is a complex infrastructure ecosystem that powers reliability, performance, measurement, and efficiency across the platform. As Pinterest grows, it’s increasingly important that we understand these systems clearly so we can make smarter decisions for both Pinners and the business. We’re looking for a Data Scientist to join our Infrastructure Data Science team. In this role, you’ll partner with engineering and cross-functional teams to make Pinterest’s infrastructure more measurable, intelligible, and actionable. Depending on the area, your work may span app performance, shopping infrastructure, metrics quality, infrastructure governance, or site reliability. You’ll help build the data foundations, measurement systems, and analytical fram

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: The Strategic Sourcing team is part of Airbnb’s Global Procurement organization and plays a key role in enabling Airbnb to operate efficiently and scale sustainably. We partner closely with internal stakeholders to design and deliver sourcing strategies that align with Airbnb’s business priorities while driving innovation, value, and stakeholder success. We are a collaborative, forward-thinking team that embraces an AI-first mindset — leveraging technology, automation, and data to simplify processes and unlock new efficiencies. Guided by Airbnb’s mission to create a world where anyone can belong, we focus on delivering value through curiosity, creativity, and integrity. Key cross-functional partners: Finance, Legal, Business Operations. The Difference You Will Make: As the Sourcing Manager supporting Engineering and Infrastructure, you will partner directly with engineering leaders to shape how Airbnb sources and manages critical technology capabilities. This role sits at the center of major technical investments, from infrastructure platforms to emerging AI technologies. You will design sourcing strategies that balance cost efficiency, engineering velocity, and long-term scalability. You will also play a key role in advancing how sourcing integrates AI and automation into its workflows. Rather than simply executing procurement processes, you will help modernize them by improving how market intelligence, supplier comparisons, and negotiation insights are generated and used in decision-making. Success in this role means helping engineering teams make faster, better technology d

About the Team OpenAI’s Legal team plays a crucial role in advancing our mission by tackling innovative and fundamental legal issues in AI. The team includes professionals from diverse legal fields—technology, AI, infrastructure, privacy, IP, corporate, employment, tax, regulatory, and litigation—who collaborate closely with colleagues across the company. If you are passionate about being a technology lawyer working on cutting-edge challenges, you’ll thrive here. About the Role We’re seeking a senior lawyer to participate in commercial legal strategy and execution across OpenAI’s fast-growing infrastructure portfolio. This is a cross-functional role that will partner closely with procurement, supply chain, partnerships, finance, and product teams to structure, negotiate, and manage the transactions that will support OpenAI’s long-term infrastructure ambitions. We’re looking for an experienced infrastructure transactions lawyer who thrives in ambiguity and wants to help define the commercial playbook for infrastructure efforts in the AI era. This role reports to the Associate General Counsel for infrastructure. 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 commercial legal strategy and risk management for OpenAI infrastructure transactions. Draft, negotiate, and advise on complex agreements with infrastructure suppliers, manufacturers, distributors, and technology partners. Support strategic partnerships involving AI infrastructure and hardware supply chains. Develop frameworks for procurement, licensing, and collaboration across the infrastructure ecosystem. Partner with finance and operations teams to align contract terms with business and compliance requirements. Collaborate with policy and regulatory colleagues on issues impacting global supply chains, export controls, and manufacturing. Build scalable, efficient contracting process

About the Team OpenAI’s Industrial Compute organization is building the infrastructure required to support the next generation of frontier AI systems. Through a combination of strategic partnerships and self-built data center campuses, we are scaling the physical infrastructure needed to deliver compute at unprecedented scale. The Commissioning organization is responsible for ensuring this infrastructure is safely tested, validated, integrated, and transitioned into reliable operations. As the portfolio grows, the team is building common standards, processes, tools, and reporting systems that allow commissioning programs to operate consistently across projects while giving teams and leadership clear visibility into readiness, risk, and execution. About the Role We are seeking a Commissioning Program Manager to build and scale the operating systems behind OpenAI’s infrastructure commissioning programs. You will own the development and continuous improvement of commissioning standards, processes, tools, dashboards, and KPIs across the infrastructure portfolio. You will work closely with commissioning and construction teams to translate field execution needs into practical playbooks, workflows, templates, metrics, and reporting mechanisms that teams can use from construction readiness through testing and turnover. This role sits at the intersection of infrastructure delivery, program management, process design, and data. The ideal candidate understands how complex construction projects operate and can turn fragmented workflows and project data into repeatable systems that improve execution without creating unnecessary administrative burden. Key Responsibilities Develop and maintain commissioning program standards, playbooks, process maps, templates, checklists, stage gates, and acceptance criteria across infrastructure projects. Establish consistent workflows for commissioning planning, construction readiness, QA/QC, issue management, document control, testing evidence

About the Team OpenAI’s Legal team plays a crucial role in advancing our mission by tackling novel and consequential legal issues in AI. The commercial infrastructure legal team supports the systems and facilities that make advanced AI possible, including compute, first-party silicon, colocation, and first-party data center development. About the Role We’re seeking a senior commercial infrastructure lawyer to lead legal work across our rapidly growing data center development and colocation portfolio. You will advise on complex, high-value transactions involving new data center sites, power, construction, colocation, and related infrastructure arrangements. This role is designed for a lawyer who understands how data centers are developed and operated—not a general real estate practitioner. You will work closely with infrastructure, finance, procurement, and operations teams, while coordinating outside counsel where appropriate, to help projects move quickly and responsibly. San Francisco is preferred, and occasional travel may be required. In this role, you will: Lead commercial legal strategy and risk management for data center development and colocation transactions. Draft, negotiate, and advise on colocation agreements, construction agreements, power-related arrangements, and other contracts supporting data center development. Support first-party projects involving raw land, site and power rights, design and construction, EPC models, third-party build-to-suit structures, and leasebacks. Partner cross-functionally with infrastructure, finance, procurement, operations, and other stakeholders on fast-moving, complex projects. Manage and collaborate effectively with outside counsel across a high volume of infrastructure matters. Develop scalable legal playbooks and contracting approaches for a growing portfolio of data center sites. You might thrive in this role if you have: 12+ years of legal experience, primarily in commercial legal roles. Deep, hands-on experience

About the Team The Industrial Compute team is responsible for building the physical infrastructure that powers OpenAI’s largest-scale AI systems. We design, deploy, and operate next-generation compute infrastructure across a rapidly expanding global footprint, combining OpenAI-owned infrastructure with strategic cloud and infrastructure partners to support frontier AI workloads. As our infrastructure footprint grows, operational excellence across third-party providers becomes increasingly critical. Our team ensures external infrastructure partners consistently deliver the reliability, performance, and operational maturity required to support OpenAI’s rapidly expanding compute environment. About the Role We are seeking a Hardware Technical Program Manager, Infrastructure Partner Operations to lead operational delivery across OpenAI’s third-party infrastructure partners, including major cloud service providers and strategic compute vendors. In this role, you will serve as the primary operational program manager for external infrastructure partners, driving accountability for service delivery, operational readiness, incident management, performance reporting, and continuous operational improvement. You will work closely with partner engineering and operations teams while coordinating internally across Hardware Engineering, Infrastructure Operations, Capacity Planning, Networking, Supply Chain, Deployment, Reliability Engineering, and executive leadership. Success in this role requires someone who understands how hyperscale infrastructure organizations operate, can establish strong operational governance with external partners, and is comfortable driving complex technical programs without direct ownership of the underlying infrastructure. Key Responsibilities Own operational engagement with third-party infrastructure providers, ensuring consistent execution against operational commitments, service-level agreements (SLAs), and performance expectations. Develop operationa

About the Team Data Platform at OpenAI owns the foundational data stack powering critical product, research, and analytics workflows. We operate some of the largest Spark compute fleets in production; design, and build data lakes and metadata systems on Iceberg and Delta with a vision toward exabyte-scale architecture; run high throughput streaming platforms on Kafka and Flink; provide orchestration with Airflow; and support ML feature engineering tooling such as Chronon. Our mission is to deliver reliable, secure, and efficient data access at scale and accelerate intelligent, AI assisted data workflows. Join us to build and operate these core platforms that underpin OpenAI products, research, and analytics. We’re not just scaling infrastructure – we’re redefining how people interact with data. Our vision includes intelligent interfaces and AI-assisted workflows that make working with data faster, more reliable, and more intuitive. About the Role This role focuses on building and operating data infrastructure that supports massive compute fleets and storage systems, designed for high performance and scalability. You’ll help design, build, and operate the next generation of data infrastructure at OpenAI. You will scale and harden big data compute and storage platforms, build and support high-throughput streaming systems, build and operate low latency data ingestions, enable secure and governed data access for ML and analytics, and design for reliability and performance at extreme scale. You will take full lifecycle ownership: architecture, implementation, production operations, and on-call participation. You’ve supported Spark, Kafka, Flink, Airflow, Trino, or Iceberg as platforms. You’re well-versed in infrastructure tooling like Terraform, experienced in debugging large-scale distributed systems, and excited about solving data infrastructure problems in the AI space. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per wee

About the team The Fleet team at OpenAI supports the computing environment that powers our cutting-edge research and product development. We oversee large-scale systems that span data centers, GPUs, networking, and more, ensuring high availability, performance, and efficiency. Our work enables OpenAI’s models to operate seamlessly at scale, supporting both internal research and external products like ChatGPT. We prioritize safety, reliability, and responsible AI deployment over unchecked growth. About the role As a software engineer on the Fleet High Performance Computing (HPC) team, you will be responsible for the reliability and uptime of all of OpenAI’s compute fleet. Minimizing hardware failure is key to research training progress and stable services, as even a single hardware hiccup can cause significant disruptions. With increasingly large supercomputers, the stakes continue to rise. Being at the forefront of technology means that we are often the pioneers in troubleshooting these state-of-the-art systems at scale. This is a unique opportunity to work with cutting-edge technologies and devise innovative solutions to maintain the health and efficiency of our supercomputing infrastructure. Our team empowers strong engineers with a high degree of autonomy and ownership, as well as ability to effect change. This role will require a keen focus on system-level comprehensive investigations and the development of automated solutions. We want people who go deep on problems, investigate as thoroughly as possible, and build automation for detection and remediation at scale. In this role, you will: Build and maintain automation systems for provisioning and managing server fleets. Develop tools to monitor server health, performance, and lifecycle events. Collaborate with clusters, networking, and infrastructure teams. Partner with external operators to ensure a high level of quality. Identify and fix performance bottlenecks and inefficiencies. Continuously improve automati

About the Team At OpenAI, we’re building safe and beneficial artificial general intelligence. We deploy our models through ChatGPT, our APIs, and other cutting-edge products. Behind the scenes, making these systems fast, reliable, and cost-efficient requires world-class infrastructure. The Caching Infrastructure team is responsible for building a caching layer that powers many critical use cases at OpenAI. We aim to provide a high-availability, multi-tenant cache platform that scales automatically with workload, minimizes tail latency, and supports a diverse range of use cases. We’re looking for an experienced engineer to help design and scale this critical infrastructure. The ideal candidate has deep experience in distributed caching systems (e.g., Redis, Memcached), networking fundamentals, and Kubernetes-based service orchestration. In This Role, You Will: Design, build, and operate OpenAI’s multi-tenant caching platform used across inference, identity, quota, and product experiences. Define the long-term vision and roadmap for caching as a core infra capability, balancing performance, durability, and cost. Collaborate with other infra teams (e.g., networking, observability, databases) and product teams to ensure our caching platform meets their needs. You Might Thrive In This Role If You: Have 5+ years of experience building and scaling distributed systems, with a strong focus on caching, load balancing, or storage systems. Have deep expertise with Redis, Memcached, or similar solutions, including clustering, durability configurations, client-side connection patterns, and performance tuning. Have production experience with Kubernetes, service meshes (e.g., Envoy), and autoscaling systems. Think rigorously about latency, reliability, throughput, and cost in designing platform capabilities. Thrive in a fast-paced environment and enjoy balancing pragmatic engineering with long-term technical excellence. About OpenAI OpenAI is an AI research and deployment company d

About the Team OpenAI, in close collaboration with our capital partners, is building the world’s most advanced AI compute infrastructure ecosystem. The InfraDev team is central to this mission, setting the strategy and executing the roadmap to scale our supercomputing footprint globally. From site planning to system integration, this team operates at the intersection of commercial, technical, and operational excellence, partnering with leaders across OpenAI and the industry. About the Role We are seeking a Strategic Sourcing Manager who is ready to take on global-scale challenges in AI compute supply and manufacturing — an opportunity to shape the future of supercomputing. As part of the Infrastructure Strategy & Delivery organization supporting Industrial Compute, OpenAI’s next-generation supercomputing platform, you will lead sourcing and strategic supplier engagements for compute infrastructure at hyperscale. This role will drive commercial strategy and supplier accountability across server platforms, accelerators, rack systems, and associated thermal & power delivery components. This is not traditional procurement — it is foundational work enabling OpenAI to deploy compute faster and more efficiently than anyone in the world, while building deeply-integrated partnerships with the global compute supply chain. Key Responsibilities Develop and execute sourcing strategies for the next generation of AI compute infrastructure in partnership with engineering and program leadership. Stay at the leading edge of industry and supply-chain trends to inform category strategy and long-range planning. Initiate, negotiate, and manage commercial agreements across OEM/ODM/JDMs for accelerators, GPUs/CPUs, server platforms, rack systems, liquid-cooling components, PSUs, and supporting mechanical/electrical subsystems. Secure capacity and optionality across a rapidly scaling compute supply chain while mitigating risk and ensuring manufacturing readiness. Partner cross-funct

About the Team The Workload team is responsible for designing and running OpenAI’s LLM training and inference infrastructure that powers frontier models at massive scale. Our systems unify how researchers train and serve models, abstracting away the complexity of performance, parallelism, and execution across vast GPU/accelerator fleets. By providing this foundation, the Workload team ensures that researchers can focus on advancing model capabilities while we handle the scale, efficiency, and reliability required to bring those models to life. About the Role We are looking for an engineer to design and implement the dataset infrastructure that powers OpenAI’s next-generation training stack. You will be responsible for building standardized dataset interfaces, scaling pipelines across thousands of GPUs, and proactively testing performance bottlenecks. In this role, you will collaborate closely with the multimodal researchers, and other infra groups to ensure datasets are unified, efficient, and easy to consume. In this role, you will: Design and maintain standardized dataset APIs, including for multimodal (MM) data that cannot fit in memory. Build proactive testing and scale validation pipelines for dataset loading at GPU scale. Collaborate with teammates to integrate datasets seamlessly into training and inference pipelines, ensuring smooth adoption and a great user experience. Document and maintain dataset interfaces so they are discoverable, consistent, and easy for other teams to adopt. Establish safeguards and validation systems to ensure datasets remain reproducible and unchanged once standardized. Debug and resolve performance bottlenecks in distributed dataset loading (e.g., straggler systems slowing global training). Provide visualization and inspection tools to surface errors, bugs, or bottlenecks in datasets. You might thrive in this role if you: Have strong engineering fundamentals with experience in distributed systems, data pipelines, or infrastructure.

About the Team ChatGPT is a rapidly evolving system: new capabilities ship continuously, product surfaces change quickly, and usage patterns shift week-to-week. Supporting that pace requires infrastructure that can handle real production constraints—high concurrency, unpredictable traffic patterns, complex dependency graphs, and frequent change. The ChatGPT Infrastructure team builds and operates the platforms that enable fast iteration without compromising performance or reliability. We design shared systems, data paths, rollout mechanisms, and reliability guardrails that teams rely on to ship changes to ChatGPT at scale. We focus on high-leverage infrastructure: primitives and “golden paths” that incorporate operational lessons as defaults, so engineers don’t need to rediscover failure modes, latency pitfalls, or integration issues each time they build something new. About the Role We’re hiring Senior and Staff Engineers to design and build infrastructure systems that underlie ChatGPT and multiply the effectiveness of teams building user experiences. This is not a support-only role. It’s a platform-building role: you’ll define interfaces, develop core abstractions, and create tooling to make safe, fast iteration the norm. Your work will reduce friction, prevent regressions, improve performance, and ensure systems scale gracefully as the product grows. Where You Can Have Impact You might work on one or more of the following areas (without being restricted to any single area): Platform foundations & frameworks: Core libraries, service frameworks, and shared components that standardize system building, integration, and evolution. Scalability & performance primitives: Patterns and infrastructure that reduce tail latency, improve throughput, and keep costs predictable as demand increases. Reliability guardrails: Mechanisms that prevent outages by design—rate limiting, load shedding, dependency isolation, backpressure, safe fallbacks, and robust regression contr

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 Role As a Director, Compute & Infrastructure FP&A, you will own and drive the monthly forecasting process for the Compute & Infrastructure org by partnering with various stakeholders across Finance, Accounting, Tax and Engineering. You will play a critical role in planning and forecasting the company’s largest and most complex cost center ( Compute & Infrastructure ). You will collaborate cross-functionally to develop long-range infrastructure investment plans, evaluate build vs. buy decisions, and ensure capital is deployed efficiently to support rapid growth. You will also provide strategic financial guidance through scenario modeling, ROI analysis, and performance tracking, enabling leadership to make high-stakes decisions under uncertainty. What You’ll Do Own compute financial planning & Forecasting. Build and manage consolidation models for GPU/CPU capacity, storage, networking, and data center investments. Translate infrastructure roadmaps into short- and long-term financial forecasts (LRP, annual planning) Coordinate closely with Corporate FP&A on timelines and process Present insights on a monthly basis to senior management. Drive infrastructure investment decisions. Evaluate build vs. buy, vendor vs. owned infrastructure, and capacity allocation tradeoffs. Develop frameworks for investment trade-offs to guide executive decision making. Build scalable tooling & reporting. Implement stakeholder-facing dashboards to track compute spend, utilization, and efficiency metrics. Improve visibility into unit economics (e.g., cost per training run, cost per inference, cost per customer). Drive forecasting accuracy & accountability. Lead budget vs. actual analysis for compute and infrastructure spend. Identify key cost drivers (utilization, pricing, efficiency gains) and reduce forecast variance. Support close & financial reporting. Partner with Accounting to ensure accurate classification of infrastructure spend (OpEx vs C

About the Team The Statsig team within OpenAI owns the experimentation, rollout, dynamic configuration, and analytics infrastructure that sits on the launch path for OpenAI products. Our systems help teams ship safely, evaluate product and model changes in production, and make high-confidence decisions from real-world usage. Statsig began as an independent company built around experimentation, feature management, and product analytics at scale. After Statsig joined OpenAI, the team began the next chapter: bringing that platform expertise and infrastructure into OpenAI as the experimentation and rollout foundation for every product we ship. This is infrastructure with a very direct product consequence. Teams working on ChatGPT, Codex, model measurement, consumer experiences including ads, business subscriptions, developer products, and shared platform systems depend on Statsig to evaluate configurations, move traffic safely, ingest experiment data, serve analytics, and roll changes forward or back when production reality demands it. We are at a critical point in the platform journey. Adoption is accelerating quickly across OpenAI, and the systems that were already important are becoming load-bearing for how the company launches. The infrastructure needs to stay fast under sharply increasing evaluation volume, reliable when more services depend on it, observable enough to debug quickly, and efficient enough to support OpenAI-wide scale. Recent SDK and server-side infrastructure work has already produced measurable wins in latency, reliability, memory usage, and compute efficiency across important services. The next phase is to make those gains systematic: a platform that can absorb rapidly growing product velocity while preserving low latency, data quality, operational safety, and developer trust. Based out of OpenAI's Bellevue office, we are a close-knit team that values in-person collaboration, technical depth, operational ownership, and building infrastructure that