Partner Business Manager Power Elite in United States

About the Team OpenAI, in close collaboration with our capital partners, is building the world’s most advanced AI infrastructure ecosystem. Our Industrial Compute organization develops and deploys large-scale AI campuses designed to support the next generation of frontier model training and inference workloads. The Hardware Operations team is responsible for ensuring the reliability, availability, and lifecycle health of OpenAI’s compute infrastructure. We partner closely with Data Center Operations, Fleet Health Engineering, Manufacturing, Network Infrastructure, Capacity Planning, and our infrastructure partners to maintain world-class operational performance across rapidly expanding AI environments. As we scale globally, we are building the operational frameworks, reliability standards, and sustaining engineering practices required to support thousands of GPUs and servers across multiple campuses. About the Role We are seeking a Datacenter Hardware Technician Lead to serve as the senior on-site technical authority for hardware reliability and fleet health at one of OpenAI’s flagship AI campuses. This role operates at the intersection of hardware operations, sustaining engineering, and fleet reliability. You will partner closely with Cloud Service Provider operations teams, OpenAI fleet-health engineers, hardware engineering teams, and OEM vendors to identify, diagnose, and resolve hardware issues affecting production systems. Beyond day-to-day operational support, you will drive root cause investigations, reliability improvement initiatives, lifecycle management programs, and operational readiness efforts. You will help establish hardware maintenance standards, operational procedures, and best practices that scale across future OpenAI infrastructure deployments. The ideal candidate combines deep hands-on datacenter hardware expertise with strong troubleshooting, failure analysis, and cross-functional leadership skills. Candidates must be able to sit onsite at our

About the Team: GTM Innovation is a product engineering team with a charter to automate 100% of digital knowledge work in OpenAI's GTM, so sellers spend more time directly with customers. AGI-level reasoning doesn’t mean organization-level transformation “just works” out of the box; orgs must be redesigned around abundant intelligence and persistent virtual coworkers. Our team builds and scales a fleet of virtual coworkers that operate as full-time members of the account team, and redefines how our human-first revenue organization interacts with their agentic teammates. About the Role We’re looking for product mindset software engineers to join the GTM Innovation team. As a product engineer on this team, you’ll help OpenAI meet the world at scale. You’ll partner closely with go-to-market teams to understand their workflows, identify leverage points, and ship novel solutions using OpenAI’s API platform. You’ll move quickly from prototype to production, and your work will directly shape how customers experience our technology in the field. This role is ideal for engineers who want to be close to users, own end-to-end outcomes, and help define entirely new categories of enterprise software. In this role, you will: Build high-impact applications and tools that accelerate OpenAI’s go-to-market efforts Work across the full product lifecycle for GTM: prototype, iterate, ship, and maintain Embed with Sales, Technical Success, and Revenue Operations to identify user needs and build for them Apply OpenAI’s models in novel ways to solve real-world customer and internal workflow problems Translate learnings into feedback for Applied and Research teams to inform product development You’ll thrive in this role if you: Have 4+ years of experience as a software/ML/product engineer working on user-facing systems Former founder, or early engineer at a startup who built a product from scratch is a plus Are fluent in Python or JavaScript and comfortable building full-stack applications

About the Team OpenAI’s mission is to ensure that artificial general intelligence (AGI) benefits all of humanity. A key part of achieving that mission is training models that deeply understand and reflect human preferences — the Human Data team is at the heart of that effort. The Human Data engineering team creates the systems that enable scalable, high-quality human feedback. These systems are essential to how OpenAI trains and improves its most advanced models. Engineers on this team collaborate closely with world-class researchers to bring alignment techniques to life — from experimental ideas to production-ready feedback loops. About the Role We’re looking for software engineers to join the Human Data team and build the platforms, prototypes, tools, and infrastructure that power how our AI models are trained, aligned, and evaluated. You’ll partner with researchers and cross-functional teams to bring alignment ideas to life, influence future model training, and shape how models interact with the real world. We’re looking for people who are excited by technical ownership, enjoy working across the stack, and are eager to solve ambiguous problems in a high-impact, fast-paced environment. 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: Build and maintain robust full-stack systems for feedback collection, data labeling, and evaluation pipelines, while maintaining high levels of security. Translate experimental alignment research into scalable production infrastructure, including inference and model training stacks. Design and iterate on user-facing tools and backend services to support high-quality data workflows Partner with researchers, engineers, and program leads to shape feedback loops and model interaction paradigms Drive infrastructure improvements that enable faster iteration and scaling across OpenAI’s frontier models, from internal r

About the Team: The Database Systems team specializes in high-performance distributed databases. Our team built Rockset, the real-time search, analytics, and vector database that powers all vector search and retrieval augmented generation (RAG) at OpenAI. In addition to retrieval, as an online database, Rockset powers core functionality across all of OpenAI's product lines and many critical internal use cases. About the Role : We are looking for engineers passionate about distributed systems, close-to-the-metal performance optimization (our core engine is written in C++), and building scalable database infrastructure from the ground up. As an engineer on the Database Systems team, you'll contribute to the core database engine, driving improvements across ingestion, query execution, indexing, and storage. You'll partner with teams across OpenAI to unlock new product capabilities and help scale online database reliability and throughput as usage grows by orders of magnitude. In this role you will: Design, build, and operate high-performance distributed systems Identify and resolve performance bottlenecks to scale infrastructure to the next order of magnitude Define long-term technical direction and guide system evolution Collaborate with product, engineering, and research teams to deliver scalable and reliable infrastructure Dig deep into complex production issues across the stack Contribute to incident response, postmortems, and best practices for system reliability You might thrive in this role if you: Have significant experience building, scaling, and optimizing distributed systems at scale Are curious about database internals, storage engines, or low-latency query systems Enjoy debugging challenging performance issues in complex, high-throughput systems Have experience operating production clusters at scale (e.g., Kubernetes or other orchestration systems) Think rigorously about scalability, correctness, and reliability Thrive in fast-paced environments with high

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

About the Team OpenAI’s Platform team powers how millions of developers and enterprises build with our models. We provide APIs and agentic solutions used by global startups and fortune 500s. We work closely with product, engineering, design, and go-to-market to build a world-class platform that pushes the frontier of AI capabilities. About the Role As a Data Scientist on the Platform team, you will drive a data-driven culture for OpenAI’s API and B2B solutions. You’ll define the metrics that matter for developer success and enterprise value, measure the impact of new models and features, and partner with PMs and engineers to improve model quality, reliability, latency, and cost. Your work will shape how thousands of products adopt agentic AI. 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 Embed with the Platform product team as a trusted partner, uncovering ways to improve developer experience, reliability, and usage growth Define north-star metrics across the developer funnel (activation, retention, growth), as well as latency/cost guardrails for new features and models Design and interpret A/B tests and controlled rollouts (e.g., new model versions, pricing/limits, new API features, new B2B products) Build source-of-truth dashboards and self-serve data tools for product, engineering, and go-to-market teams Translate product learnings into actionable feedback for Research (e.g., failure modes, eval gaps, model response quality) You might thrive in this role if you have 5+ years in a quantitative role in ambiguous, high-growth environments (platforms, APIs, or B2B products a plus) Depth in SQL and Python, with a track record proposing, designing, and running rigorous experiments Experience defining and operationalizing metrics from scratch (including reliability/latency/cost and safety) Strong cross-functional communication with PMs, enginee

About the Team OpenAI's Industrial Compute organization is building the world's most advanced AI infrastructure ecosystem. Working alongside leading cloud providers, engineering firms, construction partners, utilities, and equipment manufacturers, we are delivering hyperscale AI campuses that enable the next generation of frontier AI models. The Strategic Sourcing team develops and executes the commercial strategies that ensure our infrastructure programs have reliable access to the equipment, materials, and strategic partners needed to deliver at unprecedented scale. We partner closely with Infrastructure Delivery, Capacity Planning, Design Engineering, Hardware Operations, Finance, Legal, and our external suppliers to build a resilient global supply network capable of supporting Industrial Compute's long-term growth. As we continue expanding globally, strategic sourcing becomes a critical competitive advantage, ensuring our infrastructure programs remain cost-effective, resilient, and capable of executing against aggressive deployment timelines. About the Role We are seeking a Strategic Sourcing Manager, Data Center Infrastructure to lead sourcing strategy for the critical infrastructure systems that power Industrial Compute campuses. This role will develop commercial strategies, negotiate strategic supplier agreements, and manage relationships across engineering, construction, manufacturing, and infrastructure partners responsible for delivering mission-critical facilities. You will work closely with Infrastructure Delivery, Capacity Planning, Engineering, Finance, Construction, and external suppliers to ensure Industrial Compute has the capacity, supplier relationships, and commercial frameworks required to support rapid global expansion. The ideal candidate has experience sourcing major infrastructure systems for hyperscale data centers, mission-critical facilities, industrial construction, semiconductor manufacturing, energy infrastructure, or similarly comple

About the Team: GTM Innovation is a product engineering team with a charter to automate 100% of digital knowledge work in OpenAI's GTM, so sellers spend more time directly with customers. AGI-level reasoning doesn’t mean organization-level transformation “just works” out of the box; orgs must be redesigned around abundant intelligence and persistent virtual coworkers. Our team builds and scales a fleet of virtual coworkers that operate as full-time members of the account team, and redefines how our human-first revenue organization interacts with their agentic teammates. About the Role We’re looking for Full Stack software engineers with a product mindset to join the GTM Innovation team. As a product engineer on this team, you’ll help OpenAI meet the world at scale. You’ll partner closely with go-to-market teams to understand their workflows, identify leverage points, and ship novel solutions using OpenAI’s API platform. You’ll move quickly from prototype to production, and your work will directly shape how customers experience our technology in the field. This role is ideal for engineers who want to be close to users, own end-to-end outcomes, and help define entirely new categories of enterprise software. In this role, you will: Build high-impact applications and tools that accelerate OpenAI’s go-to-market efforts Work across the full product lifecycle for GTM: prototype, iterate, ship, and maintain Embed with Sales, Technical Success, and Revenue Operations to identify user needs and build for them Apply OpenAI’s models in novel ways to solve real-world customer and internal workflow problems Translate learnings into feedback for Applied and Research teams to inform product development You’ll thrive in this role if you: Have 4+ years of experience as a software/ML/product engineer working on user-facing systems Former founder, or early engineer at a startup who built a product from scratch is a plus Are fluent in Python or JavaScript and comfortable building full-s

About the team Online Data builds and operates Habitat, the single product surface of Online Data and the system of record for OpenAI’s online user data. As OpenAI’s scale and product requirements evolve, Habitat is becoming a full-stack, one-size-fits-most database platform with end-to-end ownership of: Provisioning and developer experience APIs and guardrails Scaling, performance, and reliability Data movement, caching, routing, and placement Privacy enforcement and access control Change Data Capture (CDC) as a first-class primitive The foundation for future storage backends You’ll work on the core online database platform behind OpenAI’s products, building and operating Habitat services that handle high-QPS, latency-sensitive workloads across regions. You’ll partner closely with internal platform and product teams to ship safe, reliable systems, then push them to be faster and more cost-efficient through better caching, routing, observability, and operational tooling. This is a critical role for engineers who like owning hard distributed-systems problems end to end and sweating the details from p99 latency to production operations at massive scale. In this role, you will Design and build core abstractions spanning storage, caching, routing, CDC, and privacy enforcement Own a major surface area end to end, from product and API design to operational excellence Improve latency, correctness, and cost efficiency for real production workloads at massive scale Build strong instrumentation, debugging workflows, and developer-first tooling Collaborate closely with internal product and infrastructure teams to understand requirements and ship pragmatic solutions Participate in an on-call rotation and raise the bar on reliability while aggressively improving performance and usability You might thrive in this role if you have A strong track record building and operating high-scale backend or data-intensive distributed systems in production Excellent systems judgment and the a

About the Team OpenAI’s mission is to ensure that general-purpose artificial intelligence benefits all of humanity. We believe that achieving our goal requires real world deployment and iteratively updating based on what we learn. The Protection Scientist Engineer, Integrity team supports this by identifying and investigating misuses of our products – especially new types of abuse. This enables our partner teams to develop data-backed product policies and build scaled safety mitigations. Precisely understanding abuse allows us to safely enable users to build useful things with our products. About the Role Protection Science Engineering is an interdisciplinary role mixing data science, machine learning, investigation, and policy/protocol development. As a Protection Scientist Engineer within Integrity and Investigations, you will be responsible for designing and building systems to proactively identify and enforce on abuse on OpenAI’s products. This includes ensuring we have robust abuse monitoring in place for new products, sustaining monitoring for existing products, and prototyping and incubating systems of defense against our highest risk harms. You will also respond to and investigate critical escalations, especially those that are not caught by our existing safety systems. This will require expert understanding of our products and data, and involves working cross-functionally with product, policy, and engineering teams. This role can be based in either our San Francisco, or NY office and includes participation in an on-call rotation that will involve resolving urgent escalations outside of normal work hours. Some investigations may involve sensitive content, including sexual, violent, or otherwise-disturbing material. In this role, you will: Scope and implement abuse monitoring requirements for new product launches. Improve processes to sustain monitoring operations for existing products, including developing approaches to automate monitoring subtasks. Prototyp

About the Team OpenAI's Industrial Compute organization is building the world's most advanced AI infrastructure ecosystem. Working alongside leading cloud providers, engineering firms, construction partners, utilities, and equipment manufacturers, we are delivering hyperscale AI campuses that enable the next generation of frontier AI models. The Strategic Sourcing team develops and executes the commercial strategies that ensure our infrastructure programs have reliable access to the equipment, materials, and strategic partners needed to deliver at unprecedented scale. We partner closely with Infrastructure Delivery, Capacity Planning, Design Engineering, Hardware Operations, Finance, Legal, and our external suppliers to build a resilient global supply network capable of supporting Industrial Compute's long-term growth. As we continue expanding globally, strategic sourcing becomes a critical competitive advantage, ensuring our infrastructure programs remain cost-effective, resilient, and capable of executing against aggressive deployment timelines. About the Role We are seeking a Strategic Sourcing Manager, Data Center Infrastructure to lead sourcing strategy for the critical infrastructure systems that power Industrial Compute campuses. This role will develop commercial strategies, negotiate strategic supplier agreements, and manage relationships across engineering, construction, manufacturing, and infrastructure partners responsible for delivering mission-critical facilities. You will work closely with Infrastructure Delivery, Capacity Planning, Engineering, Finance, Construction, and external suppliers to ensure Industrial Compute has the capacity, supplier relationships, and commercial frameworks required to support rapid global expansion. The ideal candidate has experience sourcing major infrastructure systems for hyperscale data centers, mission-critical facilities, industrial construction, semiconductor manufacturing, energy infrastructure, or similarly comple

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 OpenAI’s Inference team powers the deployment of our most advanced models - including our GPT models, 4o Image Generation, and Whisper - across a variety of platforms. Our work ensures these models are available, performant, and scalable in production, and we partner closely with Research to bring the next generation of models into the world. We're a small, fast-moving team of engineers focused on delivering a world-class developer experience while pushing the boundaries of what AI can do. We’re expanding into multimodal inference, building the infrastructure needed to serve models that handle image, audio, and other non-text modalities. These workloads are inherently more heterogeneous and experimental, involving diverse model sizes and interactions, more complex input/output formats, and tighter coordination with product and research. About the Role We’re looking for a software engineer to help us serve OpenAI’s multimodal models at scale. You’ll be part of a small team responsible for building reliable, high-performance infrastructure for serving real-time audio, image, and other MM workloads in production. This work is inherently cross-functional: you’ll collaborate directly with researchers training these models and with product teams defining new modalities of interaction. You'll build and optimize the systems that let users generate speech, understand images, and interact with models in ways far beyond text. In this role, you will: Design and implement inference infrastructure for large-scale multimodal models. Optimize systems for high-throughput, low-latency delivery of image and audio inputs and outputs. Enable experimental research workflows to transition into reliable production services. Collaborate closely with researchers, infra teams, and product engineers to deploy state-of-the-art capabilities. Contribute to system-level improvements including GPU utilization, tensor parallelism, and hardware abstraction layers. You might thrive in t

About the Team The team’s mission is to accelerate the secure evolution of agentic AI systems at OpenAI. To achieve this, the team designs, implements, and continuously refines security policies, frameworks, and controls that defend OpenAI’s most critical assets—including the user and customer data embedded within them—against the unique risks introduced by agentic AI. About the Role As a Security Engineer on the Agent Security Team , you will be at the forefront of securing OpenAI’s cutting-edge agentic AI systems. Your role will involve designing and implementing robust security frameworks, policies, and controls to safeguard OpenAI’s critical assets and ensure the safe deployment of agentic systems. You will develop comprehensive threat models, partner tightly with our Agent Infrastructure group to fortify the platforms that power OpenAI’s most advanced agentic systems, and lead efforts to enhance safety monitoring pipelines at scale. We are looking for a versatile engineer who thrives in ambiguity and can make meaningful contributions from day one. You should be prepared to ship solutions quickly while maintaining a high standard of quality and security. We’re looking for people who can drive innovative solutions that will set the industry standard for agent security. You will need to bring your expertise in securing complex systems and designing robust isolation strategies for emerging AI technologies, all while being mindful of usability. You will communicate effectively across various teams and functions, ensuring your solutions are scalable and robust while working collaboratively in an innovative environment. In this fast-paced setting, you will have the opportunity to solve complex security challenges, influence OpenAI’s security strategy, and play a pivotal role in advancing the safe and responsible deployment of agentic AI systems. You’ll be responsible for: Architecting security controls for agentic AI – design, implement, and iterate on identity, netwo

Job Description: Data Scientist, B2B Demand Generation, Growth & Measurement About the Role We are hiring a Data Scientist to lead measurement, experimentation, and decision science for B2B marketing demand generation. You will help us understand which marketing investments create incremental demand, qualified pipeline, and revenue and how to scale them efficiently. Our mandate is to build a rigorous, full-funnel view of how B2B marketing creates demand and moves prospects from awareness and engagement to qualified opportunities, closed-won revenue, and expansion. You will shape how we measure marketing impact and influence across channels, campaigns, audiences, and account segments. In this role, you will partner closely with B2B Marketing, Demand Generation, Growth, Sales, RevOps, Finance to connect marketing activity to qualified pipeline, customer acquisition, and efficient revenue growth. What You’ll Do Define north-star, leading, and guardrail metrics for B2B demand generation, including account engagement, qualified leads and opportunities, sourced and influenced pipeline, conversion rates, pipeline velocity, and incremental ARR. Design and execute measurement and experimentation strategies across channels and campaigns, using randomized tests, audience or geographic holdouts, lift studies, quasi-experimental methods, and other causal approaches suited to long B2B sales cycles. Analyze channel, audience, campaign, creative, content, landing-page, and account-segment performance to identify the drivers of qualified demand, funnel conversion, pipeline quality, and incremental revenue. Partner with Marketing, Sales, RevOps, Finance, Product, and Engineering to improve instrumentation, campaign taxonomy, CRM data quality, lead-to-account matching, and the operating cadence for acting on measurement insights. Build AI-native measurement and decision-support workflows, using LLMs and agents to synthesize campaign performance, surface growth opportunities, and h