OpenAI

Product Marketing

• Start with an objective and turn it into a sharp, insights-driven go-to-market strategy.
• Go deep on the product: understand what ChatGPT can do today, where it’s going, and what makes it truly different and special – and define a narrative for how it shows up in people’s lives.
• Work with research and strategy partners to uncover the human and cultural insights that unlock growth.
• Write marketing and creative briefs that don’t just describe what to make – they inspire ideas people want to build.
• Shape integrated campaigns across channels (brand, paid, organic, lifecycle, in-product) that drive real changes in awareness, understanding, and behavior.
• Partner with designers, writers, and creative teams to push the work from great to impactful.
• Use product data and user feedback to learn what’s working, what’s not, and where the next opportunity is – then evolve the strategy.

Product Marketing Manager, Consumer

Research Engineer

• Innovate and Build: Design and build advanced machine learning models that solve real-world problems. Bring OpenAI's research from concept to implementation, creating AI-driven applications with a direct impact.
• Collaborate with the Best: Work closely with software engineers, product managers and forward deployed engineers to understand complex business challenges, address customer concerns and deliver AI-powered solutions. Be part of a dynamic team where ideas flow freely and creativity thrives.
• Optimize and Scale: Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready. Contribute to projects that require cutting-edge technology and innovative approaches.
• Learn and Lead: Stay ahead of the curve by engaging with the latest developments in machine learning and AI. Take part in code reviews, share knowledge, and lead by example to maintain high-quality engineering practices.
• Make a Difference: Monitor and maintain deployed models to ensure they continue delivering value. Your work will directly influence how AI benefits individuals, businesses, and society at large.

Research Engineer, Machine Learning Engineer – B2B Applications

Sales

• Lead a team of sellers
• Partner with solutions to build and execute complex customer programs and projects
• Manage consumption revenue forecasts
• Closely monitor the industry landscape (people, competitors, partners, etc.) to contribute to product roadmap and other corporate strategies
• Support the recruitment and onboarding of other teammates
• Support the development of company culture

Sales Manager, Digital Natives

Human Resources

• Drive strong day-to-day HR execution
• Support performance management cycles, feedback conversations, and employee relations matters
• Be the go-to partner for frontline managers
• Help implement performance, engagement, and retention initiatives
• Triage and resolve employee relations issues
• Collaborate cross-functionally with HRBPs and COEs to ensure a high-quality employee experience

HR Business Partner, EMEA

Platform Engineer

• Architect and build new platform capabilities: turn frontier customer signal into concrete designs, implementations, and APIs that become part of the OpenAI platform.
• Incubate platform bets end-to-end: take ambiguous problems, form a crisp hypothesis, ship an initial capability, and iterate quickly based on what breaks in real usage.
• Embed with design partners to learn fast: get close to production constraints, run deep technical discovery, and translate needs into product and platform requirements.
• Partner with customer-tagged FDEs in the field: deploy and debug together, capture repeatable patterns, and convert field learnings into platform improvements.
• Design and run pilot programs: define qualification criteria for early adopters, stand up internal/external alphas, and use pilots to harden both the platform and the rollout playbook.
• Collaborate as part of cross-functional platform teams: partner closely with core product and engineering counterparts, often as a single virtual team, to align on architecture and get to production together.
• Drive adoption outcomes: measure usage, identify blockers and failure modes, and prioritize the next platform increments that unlock repeatable value.

Platform Engineer – Forward Deployed Engineering

Program Manager

• Own and improve Product Policy’s core operational processes (e.g., policy updates, cross-functional handoffs, tracking and reporting).
• Build and maintain systems to measure progress, surface risks, and ensure accountability across workstreams.
• Coordinate day-to-day execution with operations, integrity, safety, and legal partners.
• Support priority initiatives by organizing workplans, driving follow-ups, and keeping execution on track.
• Develop lightweight tools, templates, and documentation that make the team more efficient and predictable.
• Translate policy requirements into clear operational steps for partner teams.

Program Manager, Product Policy

• Define and maintain incident severity levels (SEV definitions), classification criteria, and escalation thresholds.
• Establish end-to-end incident response standards: protocols, lifecycle stages (declare → stabilize → mitigate → recover → close), and operating cadence.
• Build and maintain governance artifacts: runbooks, war room formats, reporting templates, and decision/communication standards.
• Create and operationalize notification trees, stakeholder comms templates (initial, periodic updates, recovery/closure), and executive escalation criteria.
• Define clear RACI across Facilities, Hardware Ops, Network, Security, and vendor/partner teams, including handoffs and accountability paths.
• Set and manage SLAs/OLAs for acknowledgment, escalation, containment, mitigation, and reporting.
• Implement and run incident management tooling (ticketing, paging, logging) and ensure integrations with monitoring and workflow systems.
• Establish dashboards and program health metrics to track incident performance and readiness.
• Lead readiness activities: tabletop exercises, cross-functional simulations, IC/Deputy training, and a rotating on-call IC bench with certification standards.
• Serve as Incident Commander as needed: declare severity, stand up the war room, assign functional leads, and drive structured execution under pressure.
• Maintain real-time documentation (decisions, timelines, impact scope) and ensure clear restoration objectives and scope control during active events.
• Run post-incident reviews (PIRs), validate timelines, drive structured RCA (e.g., 5 Whys, Fault Tree), and separate root cause vs contributing factors.
• Define corrective/preventative actions (CAPAs), assign accountable owners, track to verified closure, and escalate overdue actions.
• Publish trend reporting (incident taxonomy, counts by severity, MTTA/MTTR, repeat failure domains) and feed systemic gaps back into design and operations teams.

Data Center Incident Program Manager

Marketing

• Guide Integrated Campaign Strategy: Work closely with Business, Product and Marketing Strategy to develop and execute marketing campaign plan that align with business goals and span paid, owned and earned channels.
• Campaign Management: Own the end-to-end planning and execution of integrated campaigns - from brief and conceptual development to stakeholder alignment, flawless execution, launch and post-campaign analysis.
• Creative Excellence: Partner with Creative Teams - both internal and agencies - to cultivate the right space for creative risk taking in service of iconic work.
• Cross-Functional Collaboration: Partner closely with teams across Product, Product Marketing, GTM, Comms, and Global Affairs to bring campaigns to life for maximum impact.

Integrated Marketing Manager

Security Engineer

• Monitor and interpret the evolving cyber threat landscape
• Track emerging cyber TTPs, attacker innovation, threat-group behavior, and ecosystem-level shifts relevant to AI systems.
• Analyze how state actors, criminal networks, hacktivists, and hybrid actors are adapting AI tools—or targeting AI infrastructure.
• Identify structural risk patterns that may affect AI providers, customers, and downstream sectors.
• Conduct structured external research and adversarial analysis
• Use competitive intelligence, red-team style thinking, and scenario methods to explore how frontier AI capabilities could be exploited or targeted.
• Develop forward-looking assessments of how cyber threats may evolve over 6–24 months.
• Surface “unknown unknowns” and stress-test prevailing assumptions about attacker incentives, constraints, and capabilities.
• Translate external signals into strategic risk context for cross-functional teammates
• Produce concise, executive-ready intelligence estimates that articulate threat relevance, potential impact pathways, and confidence levels.
• Develop priority questions and structured risk frames that inform product, safety, security, and policy decision-making.
• Benchmark OpenAI’s risk posture against real-world incidents affecting other AI providers and adjacent technology sectors.
• Support product and ecosystem readiness
• Contribute to product reviews and safety readiness processes by outlining plausible cyber-enabled misuse or targeting modes grounded in external analysis.
• Help shape practical mitigation considerations, with clear handoffs to operational and security teams that own implementation.
• Represent OpenAI in sensitive external engagements
• Serve as a credible analytical counterpart in engagements with a range of external partners.
• Communicate OpenAI’s threat perspective and align on shared risk trends and emerging threat vectors.
• Support collaboration in ways that complement—without duplicating—incident response, investigations, or core security operations functions.

Cybersecurity Landscape Analyst

Artificial Intelligence

• Map and prioritize emerging risks
• Build and continuously refine a clear picture of emerging signals and trends that could affect the AI ecosystem through upstream and external scanning.
• Design and maintain harm taxonomies that provide foresight and warning about how AI harms and misuse may manifest over the next 0-24 months and beyond.
• Contribute to an evergreen risk register and prioritization framework that surfaces the top issues by severity, prevalence, exposure, and trajectory.
• Detect and deep dive into emerging abuse patterns
• Create comprehensive approaches to horizon scanning, competitive benchmarking, and external narrative/risk sense-making.
• Stay current on abuse trends ranging from state actor misuse to criminal activity, drawing from the work of internal organizational and cross-functional partners.
• Connect individual incidents into system-level stories about actors, incentives, product design weaknesses, and cross-product spillover–whenever possible spotting these incidents or even hypothesizing them before they hit our surfaces.
• Turn analysis into actionable risk intelligence
• Translate findings into clear, ranked risk lists and concrete proposals for mitigations that product, safety, and policy teams can execute on.
• Work with Global Affairs and Communications teams to share findings in ways that reinforce OpenAI’s role as a leader in the online safety ecosystem.
• Track whether mitigation work is landing: follow key indicators, pressure-test assumptions, and push for course corrections when the data demands it.
• Build early warning and measurement capabilities
• Help define the core metrics and signals that indicate whether AI environments are safe (e.g., key harm prevalence, severity distributions, escalation rates, brand safety issues).
• Work with data science and visualization colleagues to shape monitoring views and dashboards that highlight leading indicators and unusual changes from signals spotted off platform to determine whether these are manifesting in user behavior or abuse patterns.
• Pioneer new uses of our own technologies to scale detection and transform workflows.
• Provide strategic analysis and future-looking perspectives
• Produce concise but comprehensive strategic intelligence estimates that provide full context about a given interest area that includes confidence levels based on observed data to inform judgments and recommendations.
• Run scenario analyses that explore how AI harms might evolve over the next 6–24 months (e.g., how scam networks may use agentic AI; how state actors may seek to misuse new scientific capabilities of frontier models).
• Help design and run tabletop exercises for internal and partner audiences that distill manifest and latent risks and identify mitigations.
• Benchmark OpenAI’s risk profile and mitigations against external incidents and other platforms, highlighting gaps, strengths, and opportunities.
• Shape safety readiness for new products
• Contribute to product readiness and launch reviews by laying out expected abuse modes based on broad, upstream understanding.
• Turn risk insights into practical guidance for internal teams (product, marketing, partnerships, comms) and, where appropriate, external partners using OpenAI technologies in social and brand contexts.
• Develop reusable frameworks, playbooks, FAQs, and briefing materials that make it easier for the broader organization to understand AI risks and respond consistently.

AI Emerging Risks Analyst

Account Executive

• Lead our enterprise prospects’ journeys from consideration to purchase.
• Partner with Account Associates, Solutions Engineering and Customer Success to build and execute complex customer evaluations, demos, and pilots.
• Forecast your pipeline and targets on a weekly basis.
• Closely monitor the industry landscape (people, competitors, partners, etc.) to contribute to product roadmap and other corporate strategies.
• Collaborate with solutions, marketing, communications, business operations, people operations, finance, product management, and engineering.
• Support the recruitment and onboarding of other teammates.
• Support the development of company culture.

Account Director, Education

• Drive GTM strategy for new products from initial launch through product-market fit and scaled field adoption – defining how products are sold, deployed, and expanded.
• Partner with Sales and Success to operationalize new products in the field, shaping repeatable sales motions, deployment patterns, and account strategies across priority segments.
• Design and support customer deployments and pilots to validate value, refine product market fit, and establish scalable patterns for broader rollout.
• Establish success metrics and decision frameworks, aligning a cross-functional team (Product, Sales, Success, Marketing, Enablement, etc.) on outcomes.
• Build the GTM operating cadence to ensure the team hits agreed milestones across launch, product market fit, and scaled adoption.
• Translate customer and field insights into product feedback, providing input into prioritization, sequencing, and readiness to improve sellability, adoption, and retention.

GTM Strategy, New Products

Manager

• OpenAI is seeking a highly organized and skilled Policy Manager with exceptional writing, organizational, program management, and strategic thinking abilities to join our Global Affairs team, in the Policy Operations group.
• Responsible for coordinating the development of proactive policy positions by integrating cross-functional perspectives, documenting key decision points, trade-offs, and areas of alignment or disagreement.
• Help the team stand-up new processes and systems to program manage activities across regions and campaigns.
• Contribute to Global Affairs team’s thinking about what proactive policies to advocate for and how to best position those policies to succeed around the globe.
• Collaborate with the rest of the Global Affairs regional and functional teams, as well as with representatives from legal, product policy, research, and go-to-market.
• Build cross-regional understanding and shared resources for the Global Affairs team to use.

Policy Manager – Global Affairs

Account Manager

• Own and scale search and shopping partnerships: Drive day-to-day partnership strategy and execution across priority partners, working closely with product, engineering, research, sales, finance, legal, and marketing to align roadmaps and deliver outcomes.
• Support partnership deal execution: Support commercial negotiations from partner evaluation through launch, expansion, and renewal, including both product integrations and commercial terms.
• Operate as a cross-functional driver: Coordinate internal teams and external partners to launch, manage, and optimize partnership initiatives end-to-end.
• Serve as the internal advocate for partners, aligning product and cross-functional teams to partner goals, applying thoughtful pushback on roadmap tradeoffs, and driving accountability against agreed success metrics.
• Run partner operating cadence: Establish and manage working rhythms with partners (business reviews, planning sessions, issue resolution), escalating and aligning with senior stakeholders as needed.
• Track and communicate impact: Define success metrics, monitor performance (adoption, revenue, usage, satisfaction), and clearly communicate progress, risks, and opportunities to internal stakeholders.
• Build strong partner relationships: Serve as a primary point of contact for partner counterparts, building trust and identifying new opportunities for collaboration and growth.

Product Marketing Manager, Consumer

Research Engineer, Machine Learning Engineer – B2B Applications

Sales Manager, Digital Natives

HR Business Partner, EMEA

Platform Engineer – Forward Deployed Engineering

Program Manager, Product Policy

Data Center Incident Program Manager

Integrated Marketing Manager

Cybersecurity Landscape Analyst

AI Emerging Risks Analyst

Platform Engineer – Forward Deployed Engineering

Account Director, Education

GTM Strategy, New Products

Policy Manager – Global Affairs

Partner Manager, Growth, Commerce