Team Assembler Floater in United States

About the Team The Communications team supports OpenAI’s mission by helping the organization communicate clearly, responsibly, and effectively with external audiences. We work closely with partners across the company to navigate complex topics, manage evolving narratives, and ensure OpenAI’s communications reflect our values and long-term goals. About the Role We’re looking for an exceptional PR professional to join our nimble, high-impact team to help share our progress toward developing Artificial General Intelligence (AGI) that benefits everyone. This person will partner with the Consumer Lifestyle Communications Lead to develop sustained campaigns that shape how people understand and experience our consumer products. Working across marketing, product, community, and global communications, they will craft compelling stories and integrated campaigns that showcase our products’ creativity, usefulness, and positive impact. They will lead proactive user and seasonal storytelling that makes AI feel more relatable, trusted, and useful in everyday life. This role reports to the Consumer Lifestyle Communications Lead. 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: Lead proactive user and seasonal storytelling that makes technology matter to everyday people. Support communications campaigns that showcase ChatGPT’s distinctive benefits and capabilities for global consumer audiences. Translate technical topics into clear, compelling narratives grounded in real-world impact. Build trusted relationships with consumer and lifestyle media, and manage inbound press inquiries across a range of topics. Partner with marketing, product, community, and global communications teams to deliver integrated campaigns. Spot emerging cultural and consumer trends, and move quickly to turn the right moments into relevant, high-impact storytelling opportunities. Identif

About the Team OpenAI is at the center of some of the highest-impact multimodal work in AI. ChatGPT serves a massive global audience, and enables diverse interactions via text, speech, and visuals. As interactive surfaces grow, models also need to adapt to emerging harm, understand user intent and situational context, and respond appropriately. The Chat and Multimodal Safety team is responsible for ensuring that OpenAI’s increasingly multimodal models and products behave safely across these experiences. We develop the research, training methods, and evaluations needed to make these experiences safe. Our work sits at the frontier of responsibly deploying powerful AI, in close partnership with Personal AGI, io, model training, and product teams. About the Role As a Researcher on the Chat and Multimodal Safety team, you will help shape how frontier models perceive and reason the world, and translate that understanding into safe behavior. We’re looking for people who combine deep technical expertise with strong safety judgment. Strong candidates often bridge perception and language: they may have built vision-language models, worked on modality fusion or image encoders, developed multimodal post-training or evaluations, or advanced safety for image, video, or audio 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 to new employees. In this role, you will: Define and advance multimodal safety research for text, vision, and audio, connecting perception and semantic understanding to safe model behavior. Build training and evaluation methods for VLMs, including post-training, safety evals, and interventions that help models respond safely and appropriately in varied contexts. Collaborate closely with Personal AGI, Consumer Devices, and product/model teams to translate research into safer ambient, embedded, and personalized multimodal experiences. You might thrive in this role if you:

About the Team The Solutions Engineering team is made up of trusted technical advisors who help organizations adopt OpenAI’s technology safely, effectively, and responsibly. We partner closely with customers, Sales, Product, Engineering, and Security to translate frontier AI capabilities into practical workflows that create real-world impact. Cybersecurity is one of the most urgent areas where AI can help. As frontier models become more capable at reasoning over code, logs, infrastructure, and security evidence, organizations need guidance on how to evaluate, validate, and deploy these systems safely. Our goal is to help customers move from identifying risks to implementing solutions. About the Role We are committed to bringing together people from diverse backgrounds and perspectives who are excited to help build and deploy safe, useful AI. We are seeking a solutions engineer to partner with our Enterprise customers and ensure they achieve tangible business value from our models through the OpenAI suite of products. You will partner with senior business stakeholders to understand their pre-sales needs, guide their AI strategy, and identify the highest value use cases and applications. You will work with business and technical teams to demonstrate the value of our solutions and recommend architectural patterns to kickstart their implementation and development. You will work closely with Enterprise Sales, Security, and Product teams. We are looking for a Field Security Specialist to help security leaders and hands-on practitioners understand how OpenAI models, APIs, Codex, and agentic workflows can be applied to real cybersecurity use cases. This is a customer-facing specialist role for someone who can move fluidly between CISO-level conversations, practitioner-level technical depth, and hands-on solution design. You’ll help customers evaluate OpenAI for workflows like secure code review, vulnerability triage, threat modeling, remediation, SOC workflows, detection en

About the Team OpenAI’s Application Engineering team builds the internal products and platforms that help OpenAI operate securely and at scale. We engineer, own, and evolve OpenAI’s core productivity ecosystem, creating secure applications, integrations, automation, and reusable tooling where off-the-shelf software is not enough. Our work spans employee-facing experiences and the services, APIs, control planes, and governance that make them reliable, permission-aware, and scalable. We also act as a customer zero for OpenAI’s technology, building the enterprise foundations that let employees and agents safely access the context, tools, and actions they need. We partner closely with IT, Security, product teams, and platform providers to turn company-wide problems into durable systems, learn from real internal workflows, and help shape the products we deploy. We create paved paths that let teams move quickly without compromising security or operational quality. About the Role As a Staff Software Engineer on Agent Productivity, you will shape the foundation that enables teams to build agents with secure access to the context and capabilities they need. Slack will be the first and deepest implementation surface—and where you spend most of your time—owning its application architecture, integrations, APIs, governance, and administration automation while building patterns that extend to internal systems, identity platforms, and other enterprise applications. This is a hands-on engineering role with broad organizational impact as agents support more employee workflows. You will define platform architecture, build reusable foundations, and establish secure patterns for identity, permissions, connectivity, and operations that make agents easier to develop, deploy, and manage. In this role, you will: Own the technical strategy and architecture that enable teams to build, connect, and deploy agents quickly and safely, using Slack as the primary implementation surface. Design and

About the Team The Recursive Self-Improvement (RSI) team works across research, engineering, product, and infrastructure to build AI systems that accelerate and ultimately conduct high-quality research at OpenAI. We work to automate real research workflows and improve research productivity by building systems and feedback loops, designing evaluations, and training models to develop missing capabilities. Our work spans the full lifecycle of model training, evaluation, and deployment to help researchers move faster and tackle increasingly ambitious problems. About the Role We’re hiring research scientists , research engineers , and AI systems engineers to work on automating research at OpenAI. This role is based in San Francisco, CA. In this role, you will: Design evaluations for research judgment, hypothesis generation and testing, and long-horizon experiment execution. Turn real research workflows and model failures into data and evaluation flywheels. Improve model research capabilities through agent harnesses, synthetic data, RL environments, and model training. Build and maintain safe, reliable integrations between our models and OpenAI’s research infrastructure. Develop research agents, experiment-orchestration systems, and sandboxed runtimes that support real research workflows. Create metrics and economic models to understand RSI’s current and future effects on research productivity, model capabilities, and the safety of internal deployments. This is a high-ownership role for researchers and engineers who thrive in ambiguity, move fluidly between research and implementation, and turn emerging opportunities into rigorous, reliable, scalable results. You might thrive in this role if you: Have research or engineering experience across LLM training, model evaluations, agent systems, synthetic data, research infrastructure, or large-scale distributed systems. Are a strong generalist who can move between open-ended research and practical implementation, turning ambig

About the Team OpenAI’s Governance, Risk, and Compliance team helps ensure security and privacy are grounded in how our products and systems actually operate. Assurance Operations partners with Security, Engineering, Infrastructure, Product, Privacy, and Legal to make controls provable, risk decisions explicit, and audit readiness a result of well-designed systems. About the Role We are hiring a technical, product-minded GRC builder who can own consequential audits while improving the control and evidence systems behind them. You will build a reusable common control framework, use Codex to automate assurance work, validate changing system scope, and turn repeated audit friction into measurable improvements. We are looking for someone who questions inherited assumptions, solves novel problems creatively, works closely with engineers, and makes the next audit easier by improving the underlying system. You’ll be responsible for: Lead external, internal, customer, and certification audit work from scoping through evidence review, fieldwork, remediation, and closeout. Build a common control framework linking risk, control intent, implementation, owner, system, environment, evidence, and applicable frameworks. Validate actual scope and ownership instead of assuming last year's controls, product boundaries, or evidence remain accurate. Use Codex to build and test evidence checks, control mappings, request triage, owner workflows, monitoring, and remediation reporting. Partner with engineers on cloud architecture, identity, logging, data flows, software changes, vulnerabilities, and control effectiveness. Design maintainable, permission-aware tools that preserve source provenance, human review, and evidence integrity. Reduce repeated requests and operational burden for control owners through measurable workflow improvements. Define roadmaps, decision rights, milestones, success metrics, and clear cross-functional escalations. We’re looking for someone with: Direct ownership

About the Team The Strategic Initiatives & Operations team is in need of a Technical Program Manager (TPM) to streamline our processes, including full safety governance and integration of various safety research and mitigations into our ChatGPT, API, and any frontier models. This role is critical for driving safe deployment of our new models, synthesizing inputs from multiple stakeholders, ranging across research, product, engineering, legal and policy, and ensuring all the risks are effectively and properly monitored, mitigated or resolved. About the Role As a TPM, you will be responsible for critical tasks ranging from tracking safety research progress and risk tables to overseeing the quality of human data campaigns – acting as the connective tissue to enhance the deployment of OpenAI’s safety system. Additionally, you will create and execute a compute roadmap for your team to ensure that our top priorities are resourced while taking advantage of new opportunities to make key safety research discoveries. Your primary focus will be to ensure our models are qualified for safe deployment. 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: Manage key risk areas and corresponding stakeholders. Keep track of a stack of existing and future mitigations for every major product and model deployment. Standardize the lifecycle of risk assessment, setting safety bars, consolidating inputs from multiple stakeholders across research, product, engineering, legal and policy, pre-launch safety reviews and post-launch followup. Manage pre-launch safety reviews. Share launch calendars and key safety practices and evaluations with our key parter (i.e. Microsoft). Develop comprehensive documentation for all the safety work, including metrics, evaluations, and progress tracking across multiple teams within OpenAI. Help with publishing and open sourcing safety

ABOUT THE TEAM Critical Harm Operations sits within User Safety & Risk Operations and builds enforcement systems for Frontier Risk and Material Harm that are accurate, fast, defensible, and built to scale. The Cyber vertical turns policy into reviewer standards, calibrated judgment, quality systems, escalation paths, and automation guardrails. ABOUT THE ROLE We are looking for a senior cybersecurity practitioner and operations strategist to raise the quality, scalability, and technical rigor of our Cyber Operations. You will combine hands-on cyber judgment with systems-level operating design: resolve the hardest dual-use questions, evolve SOPs, uplift reviewers and vendors, and build practical tools and automations. This is a senior IC role. Success is not primarily cases closed; it is durable improvement in the operating model and the reviewers who run it. IN THIS ROLE, YOU WILL: Drive the Cyber Operations operating model across domain priorities, SOPs, escalation paths, quality health, vendor capability, roadmap inputs and help inform trusted access strategies. Serve as the senior cyber expert for complex or high-risk decisions across ChatGPT, API, Codex, agents, and emerging product surfaces. Translate policy ambiguity, quality misses, appeals, and reviewer disagreement into clear decision rules, calibration examples, training, and tooling requirements. Build durable operating systems and quality loops: golden sets, holdouts, double-labeling, adjudication, error taxonomies, reviewer calibration, and automation evaluations. Raise FTE and BPO capability through onboarding, certification, coaching, recurring calibration, and vendor-performance partnership. Use quality, appeals, SLA, backlog, and disagreement signals to diagnose root causes and prioritize high-leverage fixes. Build hands-on solutions—SQL analyses, scripts, dashboards, LLM eval workflows, evidence enrichment, routing logic, and lightweight automations—that improve decision quality and reduce manua

About the Team The Consumer Product Marketing team helps people understand how ChatGPT can fit into their lives. We connect customer insight with product strategy and development, working across disciplines to bring meaningful products to people around the world. Our consumer subscriptions work focuses on showing people what they get with a paid ChatGPT plan and helping them decide when upgrading makes sense. About the Role As the Product Marketing Lead, Consumer Subscriptions, you will lead the product marketing strategy for ChatGPT's consumer subscription portfolio, including Go, Plus, and Pro. You will shape how customers discover and adopt paid plans while bringing a clear customer perspective to product and business decisions about how those plans are designed and tiered. You will partner closely with Product, Pricing, and Growth to define each plan's audience, positioning, value proposition, and priority use cases, and bring evidence-backed recommendations to pricing and packaging discussions. You will be accountable for driving paid-plan adoption and will lead work across product launches, plan education, premium positioning, and the customer story on pricing and plan pages across ChatGPT.com and OpenAI.com . This role calls for an individual contributor who can turn customer, market, competitive, and behavioral insights into clear subscription strategies and customer stories. You will guide senior stakeholders through tradeoffs, align partners without formal authority, adapt positioning for global markets, build scalable frameworks, and mentor peers. Success in this role means helping more free users recognize the value of ChatGPT's paid plans and turning that understanding into measurable growth in free-to-paid conversion. 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: Lead consumer subscription product marketing across ChatGPT's p

About the Team The Growth team drives user and revenue growth across ChatGPT’s consumer and business segments as well as other OpenAI products worldwide. We operate across the full funnel - from awareness and acquisition through activation, retention, and expansion - using a combination of global performance marketing, AI-powered workflows, in-product optimization, insights, experimentation, and creative ops engineering. About the Role We are hiring a Lifecycle Lead to build the company-wide owned-channel capability that helps teams reach users with relevant, timely, and trustworthy experiences. This senior, hands-on leader will set the lifecycle strategy, partner with Engineering to build the orchestration and deployment platform, and establish the operating model that allows teams across the company to launch and improve evergreen programs safely at scale. You will sit at the intersection of platform, product, and campaign strategy. You will partner with Engineering, Product, Data Science, and Analytics on the underlying systems, and with Product Marketing Managers and other client teams to design journeys that help new, active, and returning users reach value and build durable habits. In this role, you will: Partner with product to set the company-wide vision, roadmap, and operating model for lifecycle and owned-channel engagement. Partner with Engineering, Product, Data Science, and Analytics to shape the tooling and infrastructure for identity, audiences, eligibility, consent, triggers, orchestration, decisioning, frequency, experimentation, localization, quality assurance, and observability. Define scalable deployment workflows—including self-service and centrally supported paths, intake, templates, approvals, governance, service levels, and incident response—so teams across the company can launch safely and efficiently. Partner with Product Marketing Managers and other client teams to translate audience, product, and business goals into evergreen journey stra

About the Team API Agents builds the shared agent harness, tools, and infrastructure that turn OpenAI’s frontier models into systems that can reliably complete real work. We carry the capabilities behind Codex into a much broader set of products and workflows across software engineering, research, finance, healthcare, enterprise operations, and more. Our work spans search and connected context, computer use, memory, delegation and multi-agent coordination, and safe execution. Sitting at the intersection of Research, Codex, infrastructure, and applied product teams, we build reusable agent capabilities that compound across the ecosystem. About the Role We are looking for an experienced backend software engineer to build the core systems behind the next generation of agents. You will design reliable services and abstractions that help agents find the right context, use tools and computers, retain knowledge, coordinate over long-running workflows, and take action safely. The role combines deep backend and infrastructure work with strong product judgment, with opportunities to work across agent runtimes, orchestration, search, execution environments, identity and permissions, observability, and evaluations. This is software and systems engineering rather than model training: success comes from strong backend fundamentals, high agency, and the ability to turn fast-moving research capabilities into dependable production primitives. In this role, you will: Design, build, and operate the shared agent harness and backend infrastructure that power long-running, high-value workflows across OpenAI and third-party products. Build reusable capabilities across search and connected context, computer use, memory, tool execution, delegation, subagents, and multi-agent orchestration. Establish the foundations agents need to operate safely in production, including secure execution environments, identity and permissions, observability, evaluations, reliability, and cost and latency effi

About the Team Our economics team is continuously working to improve our understanding of an AI-driven economy. About the Role We are seeking a highly technical Economist to join the OpenAI Economic Research team studying the real-world economic impacts of AI. This role is designed for economists with up to 5 years of professional experience post-Ph.D. who are interested in using novel, large-scale datasets to study how AI is reshaping economic systems. We are looking for candidates with deep expertise in at least one core domain relevant to AI’s economic impact, and an interest in contributing to a broader research agenda spanning labor markets, firm behavior, market dynamics, and macroeconomic change. This is an individual contributor role where the candidate will organize and execute on their own data-oriented projects. You will work at the intersection of economic research, data science, and public policy to produce rigorous empirical work that informs decision-makers across the public, industry, and government. Research Areas of Interest We are particularly interested in candidates with demonstrated expertise in one or more of the following areas: Economic Measurement of AI Impact (e.g., adoption trajectories, labor market transitions, productivity growth, and forecasting/scenario modeling for AI-driven economic change) Macroeconomic Implications of AI (e.g., productivity, technology diffusion, economic growth) AI and the Labor Market (e.g., employment, wages, job search, task-level impacts, skill acquisition) Applicants are not expected to have experience across all domains. We aim to build a team with complementary strengths across these areas. In this role, you will: Design and execute empirical research using large-scale observational or experimental data. Apply causal inference and/or structural modeling techniques to study AI-driven economic change. Collaborate with cross-functional teams to translate research questions into testable frameworks and applic

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

About the Team We're building the foundation for a new kind of AI coworker: persistent agents that have their own environments, can meet people wherever they work, and continue making progress for as long as a task requires. Our goal is to help individuals, teams, and organizations delegate meaningful work to AI—not just ask questions or complete a single turn. Our work brings together product, agent, and infrastructure capabilities across OpenAI. Together, we are creating always-on virtual coworkers that can carry context across tasks, operate through the right tools and channels, and deliver reliable results in real workplace environments. About the Role We’re looking for a full stack product engineer to shape how people discover, direct, and collaborate with AI coworkers. You’ll own product experiences end to end, spending roughly equal time building intuitive frontend surfaces and the backend systems that make agentic workflows persistent, reliable, and useful. You’ll work at the intersection of product engineering, design, agent capabilities, and enterprise readiness—turning rapidly evolving model and platform capabilities into experiences customers can understand, trust, and use every day. In this role, you will: Design, build, and ship full stack product experiences that help people and teams delegate meaningful work to persistent AI coworkers. Create intuitive frontend interfaces for directing agents, reviewing their progress, understanding their actions, and collaborating on the work they produce. Build backend APIs, services, and data models that support persistent agent state, asynchronous execution, orchestration, and progress reporting. Develop workflows that help agents access relevant context, use tools, and collaborate with people across workplace surfaces and channels. Partner with product, design, research, and engineering teams to turn shared capabilities into cohesive products. Build trust into the product through clear user controls, understanda

About the Team The compute infrastructure team runs the GPU fleet and large-scale compute clusters that serve the models backing ChatGPT and the API, while also supporting training workloads for our next generation models. We operate a large, modern GPU fleet and provide a unified platform for other OpenAI teams to seamlessly run production Applied AI and Research training workloads. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role You’ll own the hands-on and automation work that brings WAN, fiber, carrier, and cloud-interconnect circuits into service. Partner with network engineers, fiber providers, cloud service providers, colocation teams, and data-center technicians to move each connection from ordered and patched to verified, stable, and ready for handoff. You’ll own Layer 1 troubleshooting and circuit bring-up while building workflows that translate reliable system or model output into precise, approved technician actions, capture field feedback, and drive each connection to a green-port handoff. The right person combines strong physical-networking judgment with practical automation skills: patch-panel and port mappings, optics and light levels, provider coordination, structured operational data, API or scripting workflows, and human-in-the-loop LLM tooling. Responsibilities Own Layer 1 activation and restoration for carrier circuits, dark fiber, wavelengths, Ethernet handoffs, and dedicated cloud interconnects across data centers and points of presence. Reconcile complete A-side/Z-side as-builts: circuit IDs, LOAs/CFAs, carrier demarcations, MMR/ODF/MDF and patch-panel positions, fiber pairs, cross-connects, optics, and device ports. Investigate no-light, low-light, wrong-port, link-flap, and error-rate issues across providers and CSPs; isolate continuity, dirty connectors, polarity, incorrect patching