Partner Strategy And Operations Lead in United States

About the Team Our Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role We are seeking a Mechanical Engineer to lead the engineering, characterization, and productionization of flexible and compliant components in robotic platforms. You will partner closely with cross-functional teams to translate material concepts into engineered subsystems that meet functional, durability, and manufacturing requirements. This role focuses on understanding how soft materials behave in dynamic mechanical systems — including fatigue, creep, hysteresis, wear, and environmental degradation — and designing assemblies that perform consistently at scale. You will work with materials such as elastomers, foams, thermoplastic polyurethanes (TPUs), engineered fabrics, knitted and woven textiles, cables, and other flexible load-bearing or transmission elements, integrating them with rigid hardware, sensors, and actuators using fabrication methods such as bonding, molding, lamination, and sewn assemblies. This role is based in San Francisco, CA, and requires in-person presence 4 days a week. In this role, you will Design and integrate compliant or flexible materials into mechanical subsystems and rigid hardware interfaces. Leverage FEA tools to characterize material behavior under operational loads, including tension, compression, abrasion, fatigue, and environmental exposure. Develop test methods and validation protocols to evaluate durability, performance, and failure modes of soft components. Collaborate with cross-functional teams to transition early prototypes into manufacturable designs. Source and evaluate materials in collaboratio

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 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 OpenAI’s Hardware organization develops system and infrastructure solutions designed for the unique demands of advanced AI workloads. We work closely with architecture, infrastructure, and vendor teams to evaluate system performance and guide critical design decisions. Our team focuses on building and applying performance modeling frameworks to understand system behavior, quantify tradeoffs, and support next-generation infrastructure design. About the Role We are seeking an Performance Modeling Engineer to support the development and application of modeling tools used to evaluate AI system performance and inform architectural decisions. In this role, you will partner closely with Senior Performance Modeling Engineers and the Performance Modeling Lead to analyze system behavior, run simulations and analytical models, and help evaluate tradeoffs across compute, memory, networking, and storage. You will contribute to building modeling frameworks while developing a strong foundation in system architecture and AI infrastructure. This role is ideal for early-career engineers with 1–2 years of experience in software engineering, systems analysis, or performance modeling who are excited to grow in large-scale infrastructure and hardware/software systems. 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 Support the development and maintenance of performance modeling tools and frameworks Assist in building models to evaluate system behavior across compute, memory, networking, and interconnect subsystems Help analyze distributed system scaling behavior and identify performance bottlenecks Run simulations and analytical models to support architecture and infrastructure decisions Partner with senior engineers to evaluate design tradeoffs across hardware and system components Interpret modeling outputs and help translate findings into clear recommendations Vali

About the Team The Cooperative AI team is scaling OpenAI with OpenAI. We are building a model-powered scaled automated workforce and knowledge system that evolves and learns alongside a human workforce. By leveraging OpenAI’s state-of-the-art models and technologies, some already in production, others still in the lab, we develop systems that reason and work autonomously for a wide variety of operational work. We leverage real workloads for critical systems across finance, sales, customer support, integrity, product insights, internal operations, and more in order to drive insights into product and industry. We partner closely with internal teams and external customers globally, operating in a hyper-fast feedback loop where many of our users are just a few steps away. This proximity allows us to iterate quickly, validate impact in real time, and accelerate industry impacting learnings and systems builds. We are a highly multidisciplinary, self-contained team focused on transforming the workplace via smart systems, knowledge, scalable and reliable primitives that apply world-class AI capabilities across domains. Our mission is to learn fast and transform how humans collaborate with AI at scale. About the Role We are looking for a hands-on Engineering Manager to lead a small, fast-moving team building AI-powered automation systems that redefine how work gets done across OpenAI. This role sits at the intersection of applied AI, research, and product engineering. You’ll lead a team that builds systems that know how to learn from humans, and carry real workloads across, sales, support, finance, IT, and more, while staying deeply involved in the technical work. You will operate in a highly iterative environment, deploying systems directly to internal users, gathering rapid feedback, and evolving solutions in real time. This is a high-ownership role for someone excited about building 0→1 systems, working closely with customers, and shaping how AI transforms operational wor

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 OpenAI’s Hardware organization develops system and infrastructure solutions designed for the unique demands of advanced AI workloads. We work closely with architecture, infrastructure, and vendor teams to evaluate system performance and guide critical design decisions. Our team focuses on building and applying performance modeling frameworks to understand system behavior, quantify tradeoffs, and inform next-generation infrastructure design. About the Role We are seeking Performance Modeling Engineers to develop and apply modeling tools that evaluate AI system performance and inform architectural decisions. In this role, you will work closely with the Performance Modeling Lead and partner teams to analyze system behavior, run simulations or analytical models, and help quantify tradeoffs across compute, memory, networking, and storage. You will contribute to building modeling frameworks and applying them to real-world questions that impact system design and vendor decisions. This role is well-suited for engineers with strong software or modeling backgrounds who are interested in developing deeper expertise in system architecture and AI 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. Key Responsibilities Develop and maintain performance modeling tools and frameworks. Build models to evaluate system behavior across: compute, memory, and interconnect subsystems distributed system scaling and bottlenecks. Run simulations and analytical models to support architectural tradeoff analysis. Collaborate with performance modeling lead and system architects to answer forward-looking design questions. Analyze and interpret modeling outputs, translating results into actionable insights. Validate models against real system measurements and workload behavior. Contribute to improving modeling fidelity, usability, and scalability. Qualifications Strong software engineeri

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Snowflake Support is committed to providing world-class solutions that inspire customer confidence and ensure business continuity. The DSE is a trusted technical partner to our Priority Support customers with a strong AI-first mindset, customer management skills & technical acumen. The role will lead the drive to reinvent and transform Priority Support into a deeply engaged, proactive offering that delivers high value throughout the customer’s post-go-live journey. The DSE role blends deep technical expertise with account engagement and service delivery. The DSE provides hands-on engagement to bridge complex business problems with Snowflake’s technology solutions. The DSE partners with the customer and internal Snowflake teams to drive quick resolution of reported issues, with a focus on future case deflection and WAF principles that ultimately strengthen customer trust in Snowflake. AS A DESIGNATED SUPPORT ENGINEER AT SNOWFLAKE, YOU WILL IMPACT AND CONTRIBUTE TO THE SUCCESS OF OUR CUSTOMERS: Provide hands-on support for customer needs following Snowflake deployment - from quick start consultations, to issue resolutions, account health monitoring and critical event support. Deep understanding of the customer's product integration architecture and workloads. Design, revi

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Snowflake is seeking an Enablement Business Partner to serve as the Chief Activation Officer for our Solution Engineering team. Embedded within key leadership teams, you will accelerate field capability tied to business outcomes, owning the full spectrum of how SEs learn, from structured programs to in-the-moment performance support. You translate business problems into capability solutions, designing systems that make the field more capable when and where it matters most. IN THIS ROLE YOU WILL GET TO: Act as the strategic enablement partner for SE leadership, diagnosing skill gaps tied to business outcomes, prescribing targeted interventions, and measuring whether capability actually changed Curate and quality-gate enablement content: validate AI outputs for accuracy and audience fit, maintain a source of truth for your domains (theater and product), and feed evidence-based quality signals back to PM and PMM Diagnose field needs through signals (Gong, Salesforce, theater-level data analysis, leadership conversations, steer co themes, PM roadmap changes, etc), then classify and prioritize gaps with data Design activation experiences, picking the right modality (hands-on or self-serve lab, AI skill, peer learning, coaching nudge), and measuring behavior change, not just comp