Partner Solution Engineer in United States

About the Team OpenAI’s mission is to ensure the responsible and widespread adoption of artificial intelligence. In support of that mission, the Marketing team helps deeply understand customer audiences and market dynamics, influence the development of the right products, build sustainable and customer-aligned monetization models, and drive awareness, adoption, and usage across OpenAI’s products and platform. We take a data-driven approach to understand markets, develop monetization strategies, and uncover customer needs that shape product strategy and messaging. We partner closely with Sales, Partnerships, Product, Engineering, Research, Comms, and Design to deliver a cohesive end-to-end customer experience and lead go-to-market efforts for new product launches across channels. About the Role As a Product Marketing Manager, Research & Safety , you will shape how the world understands OpenAI’s frontier research and our approach to developing AI responsibly. You will establish the strategic narrative for some of the company’s most important research themes—including frontier capabilities, safety, preparedness, reasoning, and compute—and translate complex technical work into clear, credible stories for researchers, policymakers, and the broader public, working with cross-functional teams to translate that messaging and reach developers and enterprise. Working closely with Research, Safety Systems, Policy, Communications, and Product teams, you’ll lead the go-to-market strategy and messaging for major research and safety initiatives. You’ll develop narratives that build trust, translating technical concepts into tangible artifacts and messaging, drive industry understanding of emerging evaluation frameworks, and help communicate OpenAI’s unique perspective on responsible frontier AI development. You’ll also identify creative and non-traditional ways to bring these stories to the audiences that matter most. In this role, you will: Establish the strategic narrative f

About the Team OpenAI’s mission is to ensure that general-purpose artificial intelligence benefits all of humanity. Our Communications team’s ethos is to support OpenAI’s mission and goals by clearly and authentically explaining our technology, values, and approach to safely building powerful AI. About the Role OpenAI is seeking an experienced communications professional to join our Platform & Research Communications team. This role will work closely with the Research Communications Lead and partner deeply with safety researchers, alignment researchers, and cross-functional teams to shape how OpenAI’s safety research is understood by researchers, journalists, policymakers, and the broader public. This position is responsible for developing and executing external communications strategies around OpenAI’s safety research—from alignment and evaluations to broader work that helps advance the safe development and deployment of increasingly capable AI systems. The ideal candidate brings strong science or technical fluency, excellent storytelling instincts, and experience helping researchers communicate complex work with clarity, accuracy, and nuance. You will partner closely with research leadership, individual researchers, policy, product, safety, legal, and cross-functional communications teams. This role requires both strategic judgment and hands-on execution in a fast-moving environment where research, public understanding, and high-stakes safety narratives intersect. This role is based in San Francisco, CA and follows a hybrid schedule (three days per week in office). Relocation assistance is available. In this role, you will: Shape Safety Research Narratives Develop clear, credible external narratives around OpenAI’s safety research, including alignment, evaluations, preparedness, interpretability, and other areas connected to the safe development of frontier AI. Translate complex technical work into accessible stories without oversimplifying, overstating impact

About the Team The Software Engineering Firmware team builds reliable, high-performance systems on custom hardware. We work closely with hardware engineers to design, optimize, and ship software that bridges cutting-edge devices and real-world constraints like memory, power, and latency. Our work spans early prototyping through product launch, ensuring that our embedded platforms are robust, efficient, and production-ready. About the Role As a Firmware Engineer , you will design, implement, and debug software for embedded devices. You’ll own low-level bring-up, write production C/C++ code, and partner closely with hardware teams to deliver reliable, high-performance systems. We’re looking for engineers with deep embedded expertise, strong debugging skills, and a passion for building systems that perform under real-world conditions. This role is based in San Francisco, CA . We use a hybrid work model of four days in the office per week and offer relocation assistance to new employees. In this role, you will: Design, implement, and debug software for embedded devices. Contribute to defining software requirements, interfaces, and test plans. Bring up and debug new boards. Analyze performance, memory, and power profiles and implement optimizations. Investigate field issues, perform root-cause analysis, and deliver robust fixes. Foster good software engineering practices. You might thrive in this role if you: Have deep experience shipping embedded systems (around 10+ years). Are proficient in C and C++. Are familiar with embedded toolchains, operating systems, and debugging tools. Have experience with both rapid prototyping and scalable product development. (Nice to have) Have experience with Zephyr RTOS. (Nice to have) Have worked with networking/wireless stacks (BLE, Wi-Fi). (Nice to have) Have experience with robotic system bring-up or Linux kernel development. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose arti

About the Team The Release Engineer team is responsible for building and maintaining the systems that power software delivery—from CI/CD pipelines and artifact management to release automation and fleet telemetry. We ensure software across bootloaders, firmware, operating systems, and cloud services is built reproducibly, validated rigorously, and released safely at scale. About the Role As a Release Engineer, you’ll design, build, and operate release infrastructure that enables reliable, secure, and traceable software delivery across complex multi-component systems. You’ll partner closely with embedded, cloud, and QA teams to ensure that every build—from development to OTA deployment—is fast, verifiable, and production-ready. We’re looking for engineers who take pride in automation, build reproducibility, and system reliability—and who enjoy building the connective tissue that allows hardware and software to ship together seamlessly. This role is based in San Francisco, CA. We use a hybrid work model of four days in the office per week and offer relocation assistance to new employees. In this role, you will: Design and operate CI/CD pipelines for multi-component builds (bootloader, firmware, OS images, backend, companion apps) using hermetic toolchains. Define versioning and branching strategies; automate promotions, changelogs, and artifact retention. Integrate unit, integration, and hardware-in-the-loop (HIL) test results; quarantine flaky tests, auto-bisect failures, and block unsafe promotions. Build A/B OTA update flows with verity and health checks; run staged rollouts and canaries; implement safe rollback and roll-forward strategies. Implement code signing for binaries and firmware, generate SBOMs, run vulnerability scanning, and attach build attestations and provenance. Manage dashboards and alerts for build health, promotion latency, failure rates, and fleet update telemetry. You might thrive in this role if you: Have experience building and operating buil

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 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 research breakthroughs into real-world systems at global scale. About the Role We’re looking for an experienced Software Engineer to help build the core monetization and ads systems at OpenAI. This is a foundational role responsible for designing and implementing the infrastructure, APIs, and user-facing experiences that will power OpenAI’s next-generation monetization products—including ads. You’ll work across the full technical stack to architect, build, and ship 0→1 systems that are robust, safe, and scalable. You will collaborate deeply with Product, Design, and Research to define the future of monetized AI experiences and ensure these systems meet OpenAI’s highest standards for safety, privacy, and policy alignment. This role is exclusively based across our San Francisco and Seattle sites. We offer relocation assistance to new employees. In this role, you will: Design, build, and scale the core infrastructure behind OpenAI’s monetization and ads products Develop advertiser-facing APIs and tools that enable the cre

About the team OpenAI’s Forward Deployed Engineering (FDE) team turns research breakthroughs into production-grade systems. We embed deeply with customers to solve high-leverage problems and act as the delivery engine for our most complex large-scale engagements. We move quickly from prototype to production and surface reusable patterns that shape our platform. We operate at the intersection of deployment and development – working closely with OpenAI Research, Product and Partnerships. About the Role As a Technical Deployment Lead (TDL), you will define how OpenAI delivers complex systems to customers. You will own how they are built, shipped, and adopted. You’ll translate business outcomes into a technical plan, run day-to-day execution across FDEs, Researchers, and Customer Engineers, and partner with customer teams to ensure delivery supports their goals. You will own delivery end-to-end: embedding with customers to map workflows and success criteria, ensuring components ship on time, and leading readiness and change management for adoption. You’ll track progress, manage dependencies, make sequencing decisions, and drive 0→1 prototypes through MVP and scale. You will also share field insights with Product and Research to guide roadmap and priorities. Success will be measured first and foremost by impact - deployments that deliver measurable value against customer goals, drive adoption, and become critical to their workflows. Additional measures of success include delivery reliability (milestones hit, low reopen/churn), operating leverage (patterns reused across deployments), judgment under pressure, and product impact (field signal that shifts roadmaps/architectures). This is a high-trust, high-autonomy role. Success requires deep technical project management expertise, extreme ownership of outcomes, and an ability to immerse in customer workflows and partner with customer teams to solve complex engineering problems at pace. This role is based in San Francisco. W

About the Team OpenAI’s mission is to build safe artificial general intelligence (AGI) that benefits all of humanity. Achieving this requires bringing the world’s most exceptional talent under one roof to push the boundaries of what’s possible. Our Research Recruiting team plays a critical role in this effort. We are an embedded part of the research organization, working side by side with our research staff to deeply understand evolving priorities, build trust, and strategically shape the future of OpenAI’s talent. About the Role You will own and execute long-term talent strategies to identify, engage, and recruit many of the world’s leading and emerging AI researchers, research engineers, and technical scientists working at the frontier of machine learning. This is not a traditional execution-focused recruiting role. You will operate as a strategic partner to OpenAI’s research staff, helping define hiring priorities, shape search strategy, influence candidate evaluation, and guide hiring decisions that directly impact the direction and quality of our frontier-model research and fulfillment of our mission. In this role, you will: Partner directly with research and technical staff to define hiring priorities, shape search strategies, and anticipate future talent needs as technical roadmaps evolve. Proactively identify and cultivate exceptional AI/ML research talent across industry, academia, and emerging labs, often before formal hiring needs exist. Use market insights and candidate signals to influence hiring decisions, leveling, and compensation strategy for highly specialized research roles. Serve as a trusted advisor throughout candidate evaluation and closing — helping leaders calibrate for research excellence, long-term potential, and organizational fit. Collaborate closely with your sourcing partner to execute complex, high-impact searches in ambiguous or rapidly evolving technical domains. You might thrive in this role if you: Significant experience recruitin

About the Team The Support team is central to ensuring that our customers' experience with our products is nothing short of exceptional. We resolve complex issues, provide technical guidance, and support customers in maximizing value and adoption from deploying our products. We work closely with Sales, Technical Success, Product, Engineering and others to deliver the best possible experience to our customers at scale. OpenAI's customers represent a range of diverse backgrounds and maturity, from early-stage startups to established global enterprises. Given OpenAI’s breakneck shipping cadence and growth – and the expectation that it will only accelerate – our ability to architect automation systems and agentic workflows for scale is central to our ability to maintain exceptional support quality in the face of AGI. About the Role As a Support Vendor Manager, you will own the health, performance, and long-term scalability of multiple support partner and vendor relationships. This is a vendor leadership role first and foremost: you will drive commercial and operational accountability (SLAs, QBRs, escalation paths, remediation plans), while also building the operating model that enables support to scale without linear headcount growth. You’ll collaborate closely with User Operations teams (e.g., Trust & Safety, Fraud & Risk), Systems/Tooling, Data partners, and Product/PM stakeholders as we launch new workflow and launch and scale new programs. You’ll be responsible for: End-to-end vendor leadership: Own day-to-day oversight, relationship health, and executive-level accountability for multiple support vendors/BPOs. Performance management & remediation: Define and manage SLA/KPI performance expectations, run WBRs/QBRs, identify performance gaps, and drive structured turnaround plans with clear owners and timelines. Escalation and risk management: Serve as the primary escalation point for vendor issues, including incident response, surge events, quality regress

About the Team Like every team at OpenAI, the Marketing team contributes to our broader mission of ensuring responsible and widespread adoption of artificial intelligence. With that aim in mind, we are responsible for developing and executing strategies that drive awareness, engagement, and usage for OpenAI’s products and platform amongst our core audiences. Our focus extends beyond just promoting product features; we aim to provide valuable insights and resources that help our users make the most out of AI technologies. The Marketing Insights & Analytics team aims to understand the markets, audiences, behaviors, attitudes and needs to shape outreach strategies and inform product and business decisions. We’re the strategic partner that discovers insights, specifically: foundational understanding, marketing strategy, thought leadership, measurement and tracking. About the Role You will be the Market Research Lead that translates insights into actionable marketing plans and executions, drive business results, and orient the team towards strategic thinking to drive brand outcomes. This is critical as we hope to reach millions of users and businesses worldwide. This role can be based in San Francisco, CA or NYC, NY utilizing a hybrid work model (3 days per week in-office). In this role, you will: Play an integral part of Marketing and be a strategic partner to brand, product marketing, creative, product and beyond. Design, execute, and deliver high-impact research using mixed methods. Work on a diverse portfolio of business challenges - how do we reach the next billion people, how do we grow internationally, how do we position our suite of products, and how do we ship joy to our customers. Translate business questions into research plans. Translate data into clear, compelling narratives. Develop deep empathy for developers, builders, and technical decision-makers, understanding their workflows, motivations, and pain points across the lifecycle Shape go-to-market str

About the Role We are seeking a Cloud Infrastructure Engineer to help design and evolve the platforms that power OpenAI’s products. In this role, you will be a hands-on technical leader, driving the architecture, scalability, reliability, and security of critical infrastructure systems. You will help define how we build and operate infrastructure at the next order of magnitude, while influencing technical direction across teams. This role is both deeply technical and highly strategic, requiring strong ownership, sound judgment, and the ability to partner effectively across engineering, product, and research organizations. In this role, you will: Design and build scalable, reliable, and secure infrastructure platforms that power OpenAI products Evolve cloud infrastructure abstractions that enable rapid product development across teams Architect systems to support significant growth, performance, and operational complexity Improve server orchestration, networking, distributed systems reliability, and infrastructure security posture Influence technical direction and infrastructure strategy across multiple teams Partner closely with product, research, and engineering teams to align infrastructure with evolving needs Own operational excellence, including participation in on-call rotations, incident response, and production readiness Mentor engineers and raise the overall technical bar of the organization Contribute to a culture of high ownership, low ego, and thoughtful collaboration You might thrive in this role if you: 8+ years of experience building and operating large-scale infrastructure systems Deep expertise in Kubernetes and container orchestration at scale Strong experience designing cloud abstractions and platform infrastructure (AWS, GCP, Azure, or similar) Proven track record of leading complex technical initiatives across teams Experience operating highly reliable, secure, and scalable distributed systems Security engineering experience or security backgroun

About the Team OpenAI is building the infrastructure foundation for the next generation of AI. The Data Center Engineering team defines the strategy, reference architectures, technical requirements, and delivery standards for the large-scale data centers that support OpenAI research, products, and infrastructure partners. As a Data Center Infrastructure Engineering Program Manager, you will help turn complex infrastructure strategy into executable programs across electrical, mechanical, controls, network, hardware, construction, commissioning, deployment, and operations workstreams. You will partner with research, hardware engineering, data center engineering, site development, supply chain, security, EHS, finance, legal, operations, and external delivery partners to bring OpenAI's infrastructure vision to life. About the Role We are looking for an Engineering Program Manager (EPM) to lead assigned infrastructure programs focused on production and non-production network integration, controls coordination, and the design and deployment of data hall or whitespace facilities. The EPM will support functional Directly Responsible Individuals (DRIs) across network, controls, structural, electrical, and mechanical disciplines. Key responsibilities include coordinating assigned workstreams and program controls, maintaining risks and interfaces, and supporting readiness within the network and data hall deployment track. The ideal candidate thrives on bringing structure to complex environments characterized by ambiguous technical requirements, large partner ecosystems, tight deadlines, and high operational stakes. This individual must be adept at keeping teams aligned on decisions, risks, dependencies, schedules, and readiness criteria, and escalating gaps or decision points when needed. Candidates should have a proven track record of managing technically challenging engineering programs across major lifecycle phases, including design, validation, procurement, construction, c

About the team OpenAI’s Forward Deployed Engineering (FDE) team turns research breakthroughs into production-grade systems. We embed deeply with customers to solve high-leverage problems and act as the delivery engine for our most complex large-scale engagements. We move quickly from prototype to production and surface reusable patterns that shape our platform. We operate at the intersection of deployment and development – working closely with OpenAI Research, Product and Partnerships. About the Role As a Technical Deployment Lead (TDL), you will define how OpenAI delivers complex systems to customers. You will own how they are built, shipped, and adopted. You’ll translate business outcomes into a technical plan, run day-to-day execution across FDEs, Researchers, and Customer Engineers, and partner with customer teams to ensure delivery supports their goals. You will own delivery end-to-end: embedding with customers to map workflows and success criteria, ensuring components ship on time, and leading readiness and change management for adoption. You’ll track progress, manage dependencies, make sequencing decisions, and drive 0→1 prototypes through MVP and scale. You will also share field insights with Product and Research to guide roadmap and priorities. Success will be measured first and foremost by impact - deployments that deliver measurable value against customer goals, drive adoption, and become critical to their workflows. Additional measures of success include delivery reliability (milestones hit, low reopen/churn), operating leverage (patterns reused across deployments), judgment under pressure, and product impact (field signal that shifts roadmaps/architectures). This is a high-trust, high-autonomy role. Success requires deep technical project management expertise, extreme ownership of outcomes, and an ability to immerse in customer workflows and partner with customer teams to solve complex engineering problems at pace. This role is based in NYC. We use a hy

About the Team The GPT Infrastructure team builds systems that turn advances in model inference and optimization into reliable production capabilities. We enable OpenAI workloads to be qualified and optimized across new accelerator platforms without requiring a one-off port and tuning effort for every hardware target. Our work spans distributed systems, model execution, compilers and runtimes, performance engineering, secure partner integrations, evaluation systems, and developer tooling. We build the infrastructure that makes optimization workflows automated, reproducible, and trustworthy. About the Role We are seeking a software engineer to help build the platform that qualifies and optimizes inference workloads across heterogeneous compute environments. You will develop both OpenAI-hosted services and secure partner-side software for running long-lived optimization workflows. These workflows generate candidate kernels, runtime configurations, and serving-stack changes; compile and execute them on target hardware; verify their correctness; measure their performance; and use the results to guide further optimization. You will work across model architecture, distributed execution, compilers, runtimes, networking, and accelerator systems. A central part of the role is turning research prototypes and one-off hardware bring-up efforts into reliable, reusable infrastructure with clear contracts, reproducible results, strong observability, and well-defined security boundaries. Key Responsibilities Design, build, and operate APIs and control-plane services for long-running workload qualification and optimization campaigns, including scheduling, retries, checkpointing, resource budgets, and observability. Build secure partner-side execution and evaluation software that can compile, run, verify, profile, and benchmark candidate artifacts on accelerator hardware. Integrate model workloads, hardware profiles, compiler toolchains, runtimes, serving engines, and distributed-exe

About the Team The Artifacts team is building the AI-native creation layer for documents, spreadsheets, slide decks, dashboards, reports, analyses, and new forms of interactive work products. We are rethinking what creation looks like when models can move from an ambiguous user goal to a polished, editable artifact with strong structure, taste, correctness, and speed. This is a high-agency team working across product, infrastructure, and research. We partner closely with model training teams to shape how frontier models create artifacts, and with ChatGPT product teams to turn those capabilities into experiences that millions of people can use. The work spans full-stack product engineering, model integration, rendering and editing systems, collaboration, storage, evaluation loops, and production reliability. Our ambition is to build the premier product experience for AI-generated artifacts: starting with familiar work products like slides, sheets, and docs, then expanding into new artifact types that are only possible in an AI-native world. About the Role As Engineering Manager, Artifacts, you will lead and grow the engineering team responsible for building this product and technical foundation. You will manage a team of full-stack and infrastructure-oriented engineers, set technical direction, and stay hands-on enough to shape architecture and debug hard problems. This role sits at the intersection of product engineering, research, and infrastructure. You will partner with researchers on how models are trained and evaluated for artifact creation, with product and design on the user experience. This is a strong fit for a technical manager who wants to build and ship, not only coordinate. The team has a fast trajectory, so you will help define both the product surface and the team that builds it. In this role, you will: Lead, manage, and grow a team building AI-native artifact creation experiences across documents, spreadsheets, slide decks, and emerging artifact form

About the Team The Stargate team is responsible for building the physical infrastructure that powers large-scale AI systems. We design and deliver next-generation data centers optimized for dense compute clusters, advanced networking, and rapidly evolving hardware platforms. This work sits at the intersection of hardware engineering, systems architecture, and infrastructure execution—translating cutting-edge compute roadmaps into scalable, production-ready environments. Our teams partner across silicon vendors, server and storage OEMs, networking teams, and data center engineering organizations to bring new capacity online quickly, reliably, and at global scale. About the Role We are seeking a CPU & Storage Technical Lead to define and drive the server compute and storage architecture strategy for Stargate infrastructure. In this role, you will own technical direction across CPU platforms, memory configurations, local and disaggregated storage systems, and their integration into large-scale AI clusters. You will evaluate vendor roadmaps, lead platform tradeoff decisions, and ensure compute and storage systems are optimized for training, inference, and supporting services. You will work cross-functionally with hardware engineering, performance modeling, networking, supply chain, and deployment teams, as well as external partners such as AMD, Intel, OEMs, ODMs, and storage vendors. This is a highly strategic role for someone who can operate deeply at the component level while also driving long-range infrastructure decisions. Key Responsibilities Own CPU and storage technical strategy for Stargate compute infrastructure across current and future generations. Evaluate CPU platforms across performance, efficiency, memory bandwidth, PCIe topology, cost, and roadmap alignment. Define storage architectures for AI environments, including boot media, local NVMe, shared storage, caching tiers, metadata services, and high-performance data pipelines. Drive server platform de