Operations Business Partner Director in San Francisco

About the Team The Foundations Research team works on high-risk, high-reward ideas that could shape the next decade of AI. Our goal is to advance the science and data that enable our training and scaling efforts, with a particular focus on future frontier models. Pushing the boundaries of data, scaling laws, optimization techniques, model architectures, and efficiency improvements to propel our science. The Search team sits within Foundations, building agentic search by co-designing model–system interfaces with the core search stack (serving, indexing, retrieval) to translate model intent into reliable, real-world actions. Operating at the frontier of AI and information retrieval, the team develops large-scale systems that transform and index vast corpora, enabling models to reason over global knowledge and act dependably. In close partnership with researchers, we rapidly bring modeling breakthroughs into production and redefine how intelligent systems discover, retrieve, and synthesize information at planetary scale. About the Role We’re looking for a researcher focused on our embedding retrieval efforts. You’ll work with a a team of world-class research scientists and engineers developing foundational technology that enables models to retrieve and condition on the right information, at the right time. This includes designing new embedding training objectives, scalable vector store architectures, and dynamic indexing methods. This work will support retrieval across many OpenAI products and internal research efforts, with opportunities for scientific publication and deep technical impact. 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. Responsibilities Tackle embedding models and retrieval systems optimized for grounding, relevance, and adaptive reasoning. Collaborate with a team of researchers and engineers building end-to-end infrastructure for training, evaluati

About the Team The Privacy Engineering team builds the systems and technical foundations that govern how user data is understood, retained, accessed, and used across OpenAI. We partner with Product, Data, Infrastructure, Security, and Legal to translate policy and trust commitments into durable architecture and enforceable controls. Our work spans data inventory and mapping, classification and lineage, retention and deletion, access governance, purpose and usage controls, auditability, and lifecycle automation. We aim to make policy-aligned data handling the default while giving teams clear, reliable primitives for building and operating products at scale. About the Role We are looking for an experienced Software Engineer to drive the architecture and execution of user data governance across OpenAI. You will define technical direction, build shared platforms and controls, and lead cross-functional programs that make data flows discoverable, policies enforceable, and ownership explicit. This role is well suited to a senior engineer who can move between deep systems design and organization-wide influence, turn ambiguous requirements into pragmatic roadmaps, and operate high-trust systems end to end. This position is based in San Francisco. Relocation assistance is available. In this role, you will: Set the technical strategy and architecture for user data governance across data mapping, classification, lineage, retention, deletion, access, and permitted usage. Design and build shared services, APIs, metadata systems, and policy-enforcement mechanisms that make governance controls consistent, scalable, and auditable. Establish reliable inventories of user data, system ownership, data flows, and policy applicability across products, infrastructure, analytics, and research systems. Partner with Product, Data, Infrastructure, Security, and Legal leaders to define decision rights, translate requirements into controls, and drive adoption across teams. Own governance systems

About OpenAI OpenAI is dedicated to ensuring that artificial general intelligence (AGI) benefits all of humanity. Our mission requires building not only world-class AI models, but also the infrastructure that enables those models to be deployed reliably, efficiently, and at global scale. As demand for AI continues to grow, we are expanding the ways OpenAI can bring high-performance inference capacity online across a diverse hardware ecosystem. About the Team The GPT Infrastructure team builds software that turns advanced inference and optimization research into production products. One focus is enabling strategic infrastructure partners and accelerator vendors to qualify and onboard new compute without a bespoke porting and optimization effort for every hardware platform. We build the control planes, APIs, secure partner-side execution environments, evaluation systems, artifact pipelines, and operational tooling that make these workflows repeatable and trustworthy. The work sits at the intersection of distributed systems, AI inference, compilers and runtimes, performance engineering, security, and external partnerships. About the Role We are seeking an experienced systems generalist who can work comfortably across the stack to help build an automated inference optimization platform. Given a workload, target hardware profile, compiler and runtime context, and a trusted verifier, the system runs durable optimization campaigns that generate, compile, execute, grade, and improve candidate kernels, runtime configurations, and serving-stack changes. You will design both the OpenAI-hosted control plane and the partner-side software that evaluates candidates on real accelerator hardware. The product must keep long-running workflows reliable, make performance results reproducible, and maintain clear trust boundaries around sensitive model and hardware information. This is a deeply cross-stack role, combining strong software engineering fundamentals with systems thinking and

About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Security team protects OpenAI’s technology, people, and products. We are technical in what we build but are operational in how we do our work, and are committed to supporting all products and research at OpenAI. Our Security team tenets include: prioritizing for impact, enabling researchers, preparing for future transformative technologies, and engaging a robust security culture. About the Role As a Security Engineer on Detection & Response, you’ll help protect OpenAI’s most sensitive assets– including our intellectual property, customer data, and the infrastructure that supports them– by building and operating the systems we use to detect suspicious activity and respond effectively when it matters. You’ll work across endpoints, identity, cloud, hyperscale compute infrastructure, and datacenter-adjacent layers, partnering closely with security teams and infrastructure owners to define the telemetry and response requirements we need and building tooling and automation where it delivers the most leverage. In this role, you will: Build and evolve Detection & Response capabilities across OpenAI’s infrastructure, products, and research environments, with an emphasis on high-signal detection and reliable operational response. Engineer detection pipelines and tooling: develop rule lifecycle management, measurement/quality loops (coverage, precision, latency), tuning processes, and safe rollout patterns. Automate response and investigations by building workflows that reduce toil (triage, enrichment, containment, evidence capture) and improve time-to-understand/time-to-contain. Partner with other Security teams and system/infrastructure owners across the company to ensure new systems ship with the right telemetry, threat models, and response playbooks from day one. Define D&R requirements and drive visibility across endpoin

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

Location: San Francisco, CA (Hybrid: 4 days onsite/week). Relocation assistance available. About the Team: We build foundational platform software that enables reliable, secure, and performant products. The team works across system layers and partners closely with adjacent engineering groups to deliver robust capabilities from concept through launch. About the Role: We’re seeking a System Software Engineer to design, implement, and debug core platform components and the pipelines that build and update system images. You’ll work across operating system layers, focusing on performance, security, and deep system debugging to ship production‑grade systems. In this role, you will: Design, implement, and debug system‑level components and services across kernel and user space. Configure and maintain OS platform services (init, services, networking, security policies) and related tooling. Build and operate image and update pipelines, ensuring reliability, reproducibility, and rollback safety. Instrument and analyze performance using profiling and tracing; optimize CPU, memory, I/O, and power usage. Own platform observability and reliability: logging, crash capture, watchdogs, and diagnostics. Collaborate with cross‑functional teams to define interfaces and deliver end‑to‑end features. Establish strong engineering practices: code review, CI, reproducible builds, and release management. Partner with external suppliers to support builds and deployments. You might thrive in this role if you: Have shipped production systems software on modern operating systems. Are proficient in C/C++ and a scripting language, and comfortable with OS internals (concurrency, memory management, filesystems, networking, power management). Bring strong systems debugging skills using debuggers, tracers, profilers, and logs across kernel/user‑space boundaries. Understand configuration of platform services and interfaces, and can translate requirements into stable, well‑documented APIs. Are fluent in u

About the Team OpenAI’s Hardware organization develops system and infrastructure solutions tailored to the demands of advanced AI workloads. We work across the full stack—from silicon to system integration—partnering closely with internal teams and external vendors to define and deliver next-generation AI infrastructure. Our team focuses on defining scalable, high-performance system architectures and reference designs that balance performance, cost, and operational efficiency across rapidly evolving technologies. About the Role We are seeking a 3P Architect to define and drive rack- and cluster-level reference designs in collaboration with external partners. This role is responsible for translating workload requirements and system-level goals into concrete architectures, aligning partners on critical design attributes, and ensuring vendor roadmaps meet our infrastructure needs. You will work closely with performance modeling and internal architecture teams to evaluate tradeoffs, while owning the end-to-end definition and execution of third-party system designs. This includes identifying gaps in current technologies, driving vendor development, and shaping future infrastructure capabilities. This role requires strong system intuition, cross-functional leadership, and the ability to operate effectively across internal teams and external ecosystems. 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. Key Responsibilities Define rack- and cluster-level reference architectures for AI infrastructure deployments. Translate workload requirements into clear system design specifications and partner deliverables. Collaborate with performance modeling teams to evaluate architectural tradeoffs and system behaviors. Align internal stakeholders and external partners on critical system attributes (performance, cost, power, reliability, scalability). Identify gaps in current technology offerings and dr

About the Team The Online Data team builds and operates the core online database and indexing services for OpenAI’s production AI applications, including supporting the explosive growth of ChatGPT, the #1 AI app in the world, and Codex, the fastest growing agentic development toolset in the world. Our mission is to ensure the reliability, correctness, and scalability of our online data stack and to curate a comprehensive portfolio of services that matches the relentless ambition of OpenAI, enabling our product and research teams to build 0-100 without getting bogged down in the minutiae of multi-region, multi-cloud, exabyte-scale data infrastructure. About the Role We are seeking an Engineering Manager to lead our Online Data Systems team, responsible for our in-house database and indexing technology. This role is about shepherding a team of world-class engineers tasked with building and operating hyperscale data storage and retrieval technology. You’ll be overseeing the delivery of extremely challenging engineering work in areas like distributed query execution, multi-region federation, self-orchestrating and self-healing services, low-level performance optimization, and more. There are few companies in the world building this kind of technology in-house at this scale where you’ll still be getting in on the ground floor. Instead of being a cog in the machine spending months chasing small optimizations, you’ll play a major part of shaping our future. In this role, you will: Build, lead, and grow high-performing infrastructure engineering teams. Drive the evolution of OpenAI’s in-house online data technologies, our core, hyper-scale database systems, indexing technologies, and vector search. Anchor delivery around measurable reliability goals (SLOs, etc) to ensure system performance and resiliency is above reproach. Champion pragmatic use of agent technology to amplify execution velocity. Reduce operational toil and incident frequency through better abstractions, gua

About the Role The Engineering Acceleration Delivery / Continuous Deployment team builds and operates the systems that safely ship OpenAI’s infrastructure and product code to production. We own the deployment platform, release pipelines, and rollout safety mechanisms that allow engineers across OpenAI to deploy changes rapidly while minimizing operational risk. Our mission is to make production deployments fast, safe, and increasingly autonomous. This role sits at the intersection of developer productivity, distributed systems reliability, and large-scale infrastructure orchestration. In This Role, You Will Design and build continuous deployment infrastructure that safely rolls out changes across dozens of Kubernetes clusters and global regions. Develop systems for progressive delivery, including canary releases, staged rollouts, and automated rollback. Improve engineering velocity by reducing friction in the release pipeline and automating manual operational workflows. Work with product and infrastructure teams to ensure their services are deployable, observable, and resilient at scale. Implement and evolve deployment methodologies such as GitOps, infrastructure-as-code, and progressive delivery patterns. Build systems that automatically evaluate deployment health using metrics, logs, traces, and alerts to detect regressions and trigger safe rollbacks. Build systems that support agent-assisted or autonomous deployment workflows using modern AI tooling. Technologies commonly used in this environment include: Kubernetes for large-scale container orchestration and runtime infrastructure Python and FastAPI for internal services Terraform for infrastructure as code GitOps-based deployment workflows (e.g., ArgoCD, Flux, or similar systems) Buildkite for CI orchestration You may be a strong fit if you: Have worked with Kubernetes-based deployment systems at scale Have experience building or operating continuous deployment platforms Are familiar with GitOps tooling such as

About the Team OpenAI’s GTM Partnerships team builds a strategic, global partner ecosystem designed to accelerate customer success, enable enterprise AI adoption, and drive durable growth in support of OpenAI’s mission. We work closely across Product, Research, Sales, Legal, Communications, and regional leadership to ensure a cohesive strategy and disciplined execution with our most strategic partners. About the Role We are hiring a Partner Director, Global McKinsey Alliance to lead and scale OpenAI’s relationship with McKinsey & Company. This role will serve as the single accountable executive owner of the alliance globally. You will define the partnership strategy and operating model, translating executive alignment into scaled commercial and transformation outcomes across regions and industries. You will work closely with McKinsey’s global leadership, industry and functional practices, and technology organizations—including QuantumBlack, AI by McKinsey—to develop differentiated enterprise AI offerings, pursue complex transformation opportunities, and help customers move from strategy to production deployment and measurable value. The role carries responsibility for the health, performance, and long-term expansion of the partnership. Success requires senior executive presence, sound judgment, commercial discipline, technical fluency, and the ability to operate effectively across a complex, partner-led organization. In this role, you will: Own the global McKinsey relationship, including alliance strategy, pipeline growth, enterprise impact, deployment scale, and long-term expansion across priority industries. Define and run the partnership’s operating model across executive governance, joint planning, regional execution, opportunity management, resource allocation, and escalation. Serve as OpenAI’s senior executive counterpart to McKinsey’s global leadership and relevant industry, functional, technology, and regional leaders. Develop a differentiated alliance s

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

About the Team The Foundations Research team works on high-risk, high-reward ideas that could shape the next decade of AI. Our goal is to advance the science and data that enable our training and scaling efforts, with a particular focus on future frontier models. Pushing the boundaries of data, scaling laws, optimization techniques, model architectures, and efficiency improvements to propel our science. The Search team sits within Foundations, building agentic search by co-designing model–system interfaces with the core search stack (serving, indexing, retrieval) to translate model intent into reliable, real-world actions. Operating at the frontier of AI and information retrieval, the team develops large-scale systems that transform and index vast corpora, enabling models to reason over global knowledge and act dependably. In close partnership with researchers, we rapidly bring modeling breakthroughs into production and redefine how intelligent systems discover, retrieve, and synthesize information at planetary scale. About the Role We’re looking for a Software Engineer focused on building and scaling retrieval systems. You’ll work with a team of researchers and engineers to develop infrastructure that enables models to retrieve and act on the right information at the right time. This includes designing and operating indexing systems, retrieval pipelines, and serving layers. This work supports retrieval across OpenAI products and research, with direct impact on system performance, reliability, and scale. Responsibilities Build and scale retrieval infrastructure across indexing, serving, and query execution. Develop low-latency, high-throughput systems for real-time model interaction. Partner with research to productionize embedding and retrieval techniques. Support dense, sparse, and hybrid retrieval pipelines. Own system performance, reliability, and observability at scale. Collaborate across Pretraining, Inference, and Product teams to integrate retrieval end-to-e

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. We are looking for a Senior Financial Analyst to join the Corporate Finance team. This is the strategic, externally-oriented arm of the team — covering the board process, long range planning, capital structure, SBC and equity modeling, and enterprise-level financial strategy. You will partner closely with the CFO, Leadership, the Board, Corp Dev, and Accounting on the decisions that shape Plaid’s long-term financial trajectory. What excites us: 5+ years of work experience including financial planning & analysis, corporate finance, investment banking, private equity, strategic finance, or management consulting — ideally with tech, SaaS, or fintech exposure. Advanced financial modeling skills, with hands-on experience building long range, scenario/sensitivity, or valuation models. Strong command of consolidated financial statements, key SaaS / fintech operating metrics, and external benchmarking. Excellent communication and storytelling skills — able to move fluidly between granular model detail and an executive-level narrative for senior leaders and the Board. Proven ability to partner cross-functionally and distill complex, ambiguous topics into structured frameworks and clear

We’re looking for a strategic operator to help advance OpenAI’s life sciences capabilities and translate them into meaningful scientific and commercial impact. Working closely with research teams and external partners, you’ll identify opportunities to improve AI models, products, and supporting infrastructure, and lead partnerships and strategic initiatives that bring these capabilities into real scientific workflows. This role combines partnership development, strategic judgment, and hands-on execution. You’ll help determine where OpenAI can make the greatest contribution, identify the expertise and resources needed, and bring together the right partners to move from an idea to demonstrated impact. In this role, you will: Shape capability priorities. Work with research and cross-functional teams to identify and prioritize new life sciences capabilities, balancing scientific value, technical feasibility, and commercial potential. Build and execute partnerships. Develop data, research, and commercial partnerships with biotechnology companies, pharmaceutical organizations, and other participants in the life sciences ecosystem. Translate capabilities into real-world applications. Partner with external organizations to apply OpenAI’s technology in scientific workflows, evaluate its usefulness, and use those learnings to inform further development. Structure effective collaborations. Work with legal, finance, research, and other teams to define partnership scope, align incentives, and navigate data access, intellectual property, commercial terms, and governance. Lead strategic initiatives. Identify and own projects that advance scientific capabilities and create long-term value for OpenAI, including licensing, joint development, and new applications of AI. Drive operational execution. Establish clear objectives, milestones, and ownership; coordinate resources; and resolve obstacles across internal teams and external partners. Expand access to expertise. Identify gaps in

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Vice President, Software Engineering Overview Decision Stream is Mastercard's next-generation AI-native decisioning platform, designed to power intelligent, real-time decisions across fraud, authentication, payments, and risk. Built with a startup mindset and enterprise-scale ambition, the platform combines innovation, speed, and engineering excellence to redefine decisioning across Mastercard's global ecosystem. We are seeking a visionary and hands-on VP of Software Engineering to help build and scale the platform. This leader will partner closely with Product, Architecture, AI, and Platform Engineering teams to drive technology strategy, architecture, engineering execution, and organizational growth. What You'll Do Lead Through Technical Excellence • Serve as a senior technology leader and role model for engineering teams. • Drive architecture, design, and technology decisions across distributed systems, streaming, AI, and cloud-native platforms. • Engage deeply with engineers, architects, and product leaders to solve complex technical challenges. • Influence engineering standards, software quality, and operational excellence. Build and Scale the Platform • Help shape and deliver a highly scalable, resilient, and secure decisioning platform operating at Mastercard scale. • Balan