OpenAI

Product Manager

• Define the strategy and execute the roadmap for enterprise identity, spanning SSO, SCIM, and advanced admin controls
• Partner with customers and internal teams to design features meeting diverse enterprise security and compliance needs
• Collaborate with engineering and GTM to evolve the enterprise identity data model for complex organizational hierarchies and administration models
• Lead cross-functional efforts to integrate enterprise identity across ChatGPT, API, and new product surfaces
• Establish and track KPIs measuring product success, adoption, and reliability
• Deliver critical enterprise identity capabilities across OpenAI products, enabling secure management of users, data, and access

Product Manager – Enterprise Identity

Solutions Engineer

• Partner with Client Partners during the sales cycle to provide technical expertise that unlocks new business and accelerates deal closure
• Lead technical discovery with advertisers and agencies to understand data flows, martech stack, measurement requirements, and activation goals
• Design and recommend implementation approaches for pixels, APIs, server-to-server integrations, identity solutions, offline conversions, and measurement frameworks
• Guide advertisers through onboarding and launch readiness, ensuring successful setup of tracking, attribution, audience signals, and reporting
• Troubleshoot technical issues related to implementation, signal quality, delivery, and measurement performance
• Build demos, proofs of concept, and technical narratives demonstrating the value of OpenAI’s ads solutions
• Partner with Product and Engineering to escalate issues, advocate for customer needs, and influence roadmap priorities
• Create repeatable technical documentation, playbooks, and best practices to scale advertiser adoption globally
• Train internal sales and success teams on technical capabilities, integrations, and evolving product features
• Collaborate with Client Partners, Customer Success Managers, Product, Engineering, Policy, and Operations teams

Solutions Engineer, Ads Solutions

Account Executive

• Own a portfolio of large enterprise accounts and develop strategies driving new business, adoption, and expansion
• Create demand through proactive prospecting, executive outreach, and understanding customer priorities
• Own complex deals end to end, including opportunity development, qualification, business case creation, technical evaluation, negotiation, and close
• Help senior executives understand AI’s potential, identify priorities, and align on investment and deployment roadmaps
• Build relationships across business units and functions, connecting executive sponsors, business leaders, technical teams, and procurement
• Partner with solutions engineering to translate technical capabilities into customer programs with measurable business outcomes
• Win initial deployments and expand successful use cases across teams, business units, and geographies
• Own a consumption revenue target and drive production usage and sustained growth across the customer lifecycle
• Maintain account plans, opportunity management, and revenue forecasts; resolve obstacles
• Bring customer and market insights to product, engineering, and GTM teams
• Help build processes, practices, and culture for a growing sales organization

Account Director, Large Enterprise

Engineer

• Own technical delivery across multiple deployments from first prototype to stable production
• Build full-stack systems that deliver customer value
• Embed closely with customer teams, understand their needs, and guide adoption
• Scope work, sequence delivery, and remove blockers early
• Make trade-offs between scope, speed, and quality; adjust plans to protect delivery
• Contribute directly in the code when progress or clarity depends on it
• Codify working patterns into tools, playbooks, or reusable building blocks
• Share field feedback with Research and Product about model successes and improvement areas
• Keep teams moving through clarity and follow-through
• Partner with customers to turn research breakthroughs into production systems
• Surface patterns that shape the platform

Forward Deployed Engineer

• Set positioning for OpenAI’s business products, connecting capabilities to customer needs, enabled work, and supporting evidence
• Lead business storytelling for priority launches across Codex, ChatGPT Work, API and developer capabilities, agents, and other enterprise products
• Build a sustained editorial program using customer stories, explainers, and executive perspectives
• Turn complex product developments into clear, accurate stories for buyers, builders, and assessors
• Build relationships with reporters and influential voices in enterprise technology
• Drive launch execution from messaging and customer proof through spokesperson preparation, media outreach, and response analysis
• Advise senior partners on the business story and clarify ownership and expert review
• Collaborate with Product, Research, Marketing, Sales, and Product Communications teams
• Report to the Head of Business Communications

Business Communications Lead, Product

Compliance

• Map and prioritize regulatory and legislative developments across jurisdictions and AI issue areas
• Distinguish enacted requirements, proposals, guidance, and emerging expectations
• Assess regulatory relevance, uncertainty, timing, and implications for models and products
• Translate external developments into actionable research questions, evaluation needs, product requirements, and policy recommendations
• Identify evidence gaps, define intended outcomes and acceptance criteria, and clarify tradeoffs and open questions
• Advise Product, Engineering, Research, and Safety teams throughout design, launch, and iteration
• Partner with Legal on legal interpretation and applicability
• Partner with Global Affairs on legislative context and external engagement
• Develop feasible implementation options and clear ownership
• Maintain traceability from external signals to internal decisions, requirements, and implementation
• Track material changes, dependencies, and emerging risks
• Use research, product evidence, and expert input to refine recommendations and inform external policy discussions

Senior Product Policy Lead – Regulation

• Own end-to-end demo readiness for new and priority product capabilities, including environments, integrations, synthetic data, evaluations, reliability checks, and fallback paths
• Build prototypes, LLM agents, and reference flows that make complex capabilities tangible and connect them to customer outcomes
• Convert recurring needs into reusable accelerators, including companion apps, templates, LLM Skills and Plugins, and self-service demo packages
• Work with GTM partners on high-impact customer moments and unblock critical technical gaps
• Identify recurring patterns that should scale across customer-facing teams
• Build internal agentic systems that automate demo preparation, validation, and asset maintenance
• Translate recurring feedback into product insights, launch-readiness priorities, and systemic improvements with Product and Engineering
• Define and raise demo quality standards for accuracy, safety, reliability, usability, and adoption

Demo Experience Engineer, Technical Success

Financial Planning and Analysis

• Build and run a best-in-class financial reporting engine
• Modernize reporting workflows through integration of ChatGPT, Codex, and proprietary AI tools
• Prepare GAAP financial statements, footnotes, and supporting schedules
• Maintain rollforwards, tie-outs, and internal consistency checks
• Partner with external auditors on PBC coordination, support quality, issue resolution, and audit execution
• Lead close-to-reporting tie-outs and document variances
• Collaborate with Accounting, FP&A, Tax, Legal, and Investor Relations
• Translate technical accounting conclusions, analyses, and audit feedback into disclosures, memos, and leadership-ready summaries
• Identify and implement process improvements, standard templates, control points, and automation
• Improve reporting workflows, data flows, scalability, and output quality

Senior Manager, Financial Reporting

Product Adoption Specialist

• Design, build, and own scalable systems for launch readiness, feedback capture, triage, synthesis, and routing
• Coordinate product launches across internal User Operations teams and external third-party teams
• Develop and implement scalable feedback loops between support teams and Product/Engineering teams
• Advocate for user needs and pain points in product and engineering discussions
• Collaborate with Product, Engineering, Marketing, and Operations to align on launch goals and timelines
• Document and standardize launch procedures for repeatable, scalable execution
• Monitor post-launch performance and gather support-team data to evaluate product impact
• Identify rollout risks and challenges and propose mitigation solutions
• Report on feedback-loop performance, insights, trends, and recommendations for the product roadmap

Product Engagement Specialist, User Operations

• Design and ship production AI systems around models
• Own integrations, data flows, reliability, observability, and on-call readiness across financial workflows
• Lead discovery and scoping from pre-sales through post-production
• Translate ambiguous business problems into hypothesis-driven problem framing, system requirements, and delivery plans with measurable outcomes
• Define and enforce launch criteria for regulated financial environments, including controls, audit artifacts, evaluation benchmarks, and acceptance thresholds
• Build in sensitive data environments where access controls, data lineage, explainability, and failure modes shape architecture and operating procedures
• Run evaluation loops measuring model and system quality against workflow-specific financial benchmarks
• Use evaluation results to drive iteration
• Own delivery state across multiple workstreams and balance scope, speed, and quality
• Distill deployment learnings into hardened primitives, reference architectures, playbooks, and tooling
• Surface field feedback informing model behavior, product capabilities, and platform gaps
• Collaborate with Product, Research, GTM, Security, Legal, and GRC

Forward Deployed Engineer, Financial Services

Marketing

• Build and execute field marketing plans aligned to priority seller groups, strategic accounts, industries, and regions
• Partner with Sales leadership on account prioritization, territory planning, outreach strategy, pipeline goals, and follow-through
• Own the full lifecycle of field programs, from strategy and planning through execution, seller enablement, follow-up, and measurement
• Run customer programs including executive dinners, roundtables, forums, workshops, industry moments, roadshows, and third-party conference activations
• Turn marquee moments into measurable pipeline opportunities with target accounts, success metrics, seller ownership, and post-event conversion plans
• Collaborate with Product Marketing, Events, Comms, Marketing Operations, Solutions, Customer Success, Partnerships, and executive stakeholders
• Track performance, communicate business impact, and build repeatable playbooks to scale field marketing across enterprise segments

Enterprise Field Marketer

Customer Success Manager

• Own relationships with a portfolio of advertising partners as their primary point of contact
• Guide advertisers through onboarding and campaign launches
• Ensure strong adoption of OpenAI’s advertising products
• Analyze campaign performance and provide actionable recommendations
• Identify opportunities to expand partnerships through product adoption and incremental investment
• Partner with Sales, Product, Analytics, Policy, and Operations to resolve issues and enhance platform value
• Surface advertiser feedback and insights to inform product improvements and long-term strategy
• Build scalable processes and best practices supporting the growth of OpenAI’s advertising ecosystem

Customer Success Manager – Ads Solutions

AI Engineer

• Partner directly with quantitative investment and trading firms to identify opportunities across research, data analysis, and software development
• Translate customer needs into practical implementations, evaluations, and measurable outcomes
• Design, build, and deploy AI systems that solve customer problems and produce measurable business outcomes
• Build prototypes, evaluation harnesses, reference implementations, integrations, and production accelerators
• Make technical decisions across models, agents, retrieval, tools, data, reliability, observability, latency, cost, safety, security, and governance
• Diagnose implementation challenges, reproduce failures, test hypotheses, and resolve blockers
• Help customers progress from prototypes to reliable production systems, sustained adoption, and scaled impact
• Lead technical workshops and hands-on sessions for quantitative researchers and engineers
• Translate deployment experience, evaluations, and feedback into requirements for Product, Research, and Engineering
• Create reusable architectures, tooling, playbooks, and technical guidance for future enterprise deployments

Applied AI Engineer, Quants

Engineering Manager

• Lead, coach, and grow a team of approximately 9–10 engineers
• Create clarity, accountability, and a healthy execution rhythm
• Own the engineering roadmap for Library
• Partner with product and design to prioritize high-impact problems
• Set standards for product quality, technical excellence, reliability, privacy, and user trust
• Provide hands-on technical leadership through architecture reviews, prototyping, debugging, and coding
• Build systems that allow AI products to persist, retrieve, and use personal and organizational context
• Partner across Personalization, model, research, infrastructure, enterprise, and third-party integration teams
• Navigate ambiguity and turn emerging AI capabilities into product and engineering plans
• Hire exceptional engineers and develop technical leaders

Engineering Manager, Libraries

Support Engineer

• Set the strategy, charter, service model, priorities, and growth plan for Dedicated Support Engineering
• Build and develop a high-performing global organization by hiring and coaching senior technical talent
• Design the customer engagement model, including customer assignment, account knowledge, operational reviews, and critical-event preparation
• Define responsibilities and handoffs with Support, Technical Success, Sales, and Engineering
• Establish standards for evidence-based troubleshooting, reproduction, systems-level investigation, mitigation, and Engineering escalation
• Build proactive reliability practices for assessing customer architectures and dependencies, identifying risks, and preparing for launches, migrations, and traffic growth
• Ensure incident learnings result in completed corrective actions
• Lead critical customer situations as a senior escalation point and align responders across teams
• Communicate clearly with customer executives and maintain accountability through mitigation, resolution, and follow-through
• Own capacity plans, coverage arrangements, investment proposals, delivery quality, and sustainable growth
• Define and measure investigation quality, time to mitigation, recurring issue reduction, customer confidence, and proactive risk reduction
• Translate customer investigations into evidence-backed recommendations for product and engineering priorities
• Apply AI and automation to preserve customer context, accelerate investigations, detect risks, and automate repeatable work
• Establish evaluations and human oversight for AI-enabled support capabilities