OpenAI

General Counsel

• Serve as commercial legal lead for Marketing from concept through launch
• Partner with Brand, Creative, Product Marketing, Design, Film and Photo, Performance Marketing, Partner Marketing, Communications, and regional teams
• Draft and negotiate agency, production, talent and creator, sponsorship, event, media, content-licensing, marketing-technology, and vendor agreements
• Structure and clear campaign and content rights, including releases, publicity and likeness rights, user-generated content, copyright and trademark permissions, music, artwork, locations, footage, and media use
• Counsel on campaign execution, public claims and disclosures, endorsements, promotions and offers, social and paid media
• Support talent, creator, partner, sponsorship, event, and launch matters
• Identify blockers, calibrate risk, and propose workable alternatives
• Manage matters through intake, vendor onboarding, review, approval, signature, and launch
• Develop templates, playbooks, training, and workflows for scalable legal support
• Monitor advertising, consumer-protection, endorsement, privacy, platform, and AI-transparency requirements and provide guidance to global teams

Deputy General Counsel, Commercial – Marketing

Financial Planning and Analysis

• Define the quality bar for AI-assisted investment banking work across research, financial analysis, valuation, modeling, diligence, transaction execution, and client materials
• Translate real banking workflows into challenging evaluation tasks with realistic inputs, constraints, deliverables, and success criteria
• Create and refine banker-grade reference artifacts, including financial models, valuation analyses, diligence materials, screening outputs, pitch books, committee materials, and transaction documents
• Develop rigorous rubrics and grading methods assessing financial correctness, analytical judgment, source quality, traceability, internal consistency, presentation quality, and practical usefulness
• Evaluate model outputs and end-to-end agent workflows, identify recurring failure modes, and provide actionable feedback to Research, Engineering, and Product
• Partner with researchers and engineers on evals, graders, datasets, human-review processes, tools, and product integrations
• Work with product teams to identify high-value AI opportunities in investment banking, prototype workflows using OpenAI tools, and assess early experiences
• Engage customers, design partners, and domain reviewers to understand standards and constraints, support testing and adoption, codify domain knowledge, and ensure responsible financial-services deployment

Subject Matter Expert, Investment Banking

QA Engineer

• Establish, implement, and manage a manufacturing-focused quality program for datacenter infrastructure
• Oversee vendors, quality assurance, process improvement, and issue resolution for critical systems
• Conduct manufacturing evaluations and audits across production, inspection, testing, and delivery phases
• Develop and track quality metrics to assess manufacturing performance and identify trends
• Partner with vendors to refine processes, training, and quality controls before shipment
• Develop and maintain a datacenter-focused manufacturing quality program supporting global deployment schedules
• Integrate manufacturing quality requirements into sourcing, design, and construction processes
• Establish cross-functional communication between manufacturing sites, construction teams, and operations
• Guide vendor and contractor quality teams to ensure adherence to OpenAI standards and specifications
• Collaborate with engineering, sourcing, construction, and operations to align quality processes with project goals
• Mentor vendor teams and provide structured feedback for continuous improvement
• Audit vendor and project-site quality activities for compliance
• Lead corrective and preventive action plans for audit findings and quality nonconformances
• Facilitate root cause analysis and drive systemic process improvements
• Monitor manufacturing schedules for on-time delivery to datacenter sites
• Ensure testing and inspection documentation is complete, accurate, and aligned with project milestones
• Participate in project quality, commissioning, and operational readiness meetings
• Travel 40–60% to manufacturing sites, datacenter locations, and partner facilities

Manufacturing Quality Engineer – Datacenter Infrastructure

Full-stack Engineer

• Design and build software systems serving as the system of record for Industrial Compute planning and operations
• Develop backend services, APIs, workflows, and data platforms for capacity forecasting, allocation, deployment readiness, and operational planning
• Connect infrastructure delivery, fleet health, capacity utilization, product demand, and financial planning into a shared operational view
• Build planning and scenario-modeling systems for tradeoffs across capacity, utilization, cost, reliability, launch timing, and business impact
• Create workflow automation and decision-support tooling to improve planning accuracy and reduce operational overhead
• Partner with Capacity Planning, Fleet Operations, Product, Finance, Infrastructure Engineering, Supply Chain, and Strategic Sourcing teams
• Drive architecture decisions across planning platforms, operational tooling, and internal infrastructure systems
• Improve data quality, observability, and operational visibility across Industrial Compute programs
• Build extensible software foundations that scale with OpenAI’s growing infrastructure footprint

Capacity Systems Software Engineer

AI Engineer

• Serve as the primary technical advisor and long-term technical relationship owner for a named portfolio of existing customers and pre-sales prospects
• Partner with Account Directors on account strategy while owning the technical account plan, technical milestones, adoption priorities, and expansion opportunities
• Lead discovery with executives and technical teams to identify, qualify, and prioritize use cases tied to meaningful business outcomes
• Develop Applied AI Architectures spanning models, applications, data, integration, security, privacy, governance, evaluation, and deployment
• Guide customers through technical evaluations, demonstrations, workshops, prototypes, and proofs of value
• Maintain a focused use-case portfolio with decision criteria, ownership, blockers, success measures, delivery needs, and adoption plans
• Develop trusted relationships and technical champions across CTOs, CIOs, CISOs, AI leaders, engineering teams, and other stakeholders
• Qualify and coordinate support from deployment engineering, implementation, training and enablement, product and domain specialists, partners, and delivery teams
• Remain accountable for technical progress and customer outcomes while ensuring delivery teams own implementation execution
• Track adoption, usage, account health, production readiness, and measurable customer impact
• Apply Retail expertise to recognize repeatable patterns, sharpen customer priorities, and identify expansion opportunities
• Share customer insights with Product, Engineering, and Research to improve products, architecture guidance, and reusable practices

Applied AI Architect, Retail

Operations

• Develop and maintain a comprehensive sustainability strategy for OpenAI’s global compute infrastructure
• Translate sustainability objectives into requirements for site selection, design, construction, procurement, commissioning, and operations
• Establish decision frameworks balancing environmental impact with reliability, deployment speed, cost, and scalability
• Develop strategies addressing operational and embodied carbon, water stewardship, materials, construction impacts, waste, circularity, and equipment lifecycle management
• Partner with data center engineering and operations teams to improve infrastructure efficiency, resource use, resilience, and operational performance
• Incorporate sustainability into self-build, colocation, cloud, and strategic infrastructure-partner decisions
• Establish goals, metrics, dashboards, and governance for infrastructure sustainability programs
• Improve the quality, consistency, and auditability of environmental and operational data
• Develop supplier requirements and lifecycle strategies for infrastructure equipment with hardware, manufacturing, and supply chain teams
• Evaluate emerging technologies, design approaches, and operating practices for scaled deployment
• Develop business cases communicating environmental impact, implementation requirements, cost, schedule, and operational tradeoffs
• Partner with Public Policy and Government Affairs on sustainability positions, regulatory developments, and external engagement
• Represent OpenAI with infrastructure partners, industry organizations, policymakers, community stakeholders, and other external parties
• Provide executive leadership with assessments of progress, risks, strategic choices, and recommended actions
• Build repeatable sustainability playbooks across sites, geographies, partners, and technology generations

Infrastructure Operations Lead – Sustainability

Planner

• Develop and maintain a multi-year portfolio plan for data center shell capacity across priority geographies
• Translate compute forecasts, IT-load requirements, rack-density assumptions, power schedules, cooling requirements, and deployment timelines into site and building requirements
• Determine when shell capacity must be secured, designed, constructed, commissioned, and ready for technical fit-out
• Integrate land, utility, interconnection, permitting, design, procurement, construction, commissioning, and network-readiness schedules into a single capacity view
• Identify capacity gaps, schedule conflicts, stranded-capacity risks, and dependencies that could prevent infrastructure from becoming operational on time
• Develop scenario models comparing self-build, lease, colocation, and strategic development-partner options
• Evaluate delivery pathways based on schedule, cost, control, flexibility, reliability, scalability, and execution risk
• Recommend campus, building, and utility phasing that preserves optionality while supporting near-term deployment requirements
• Assess third-party proposals, facilities, schedules, technical specifications, and commercial structures against OpenAI’s requirements
• Partner with capacity planning, energy, real estate, site development, design, construction, commissioning, networking, finance, legal, and commercial teams
• Establish planning assumptions, readiness criteria, decision gates, and governance for moving opportunities into execution
• Build dashboards and executive-ready materials communicating capacity supply, demand, timing, assumptions, dependencies, and material risks
• Support investment, build-versus-partner, geographic-prioritization, and portfolio-allocation decisions
• Create repeatable planning frameworks and playbooks for scaling shell-capacity decisions across regions and infrastructure generations

Development Planner, Industrial Compute

• Design, implement, and scale comprehensive enablement programs for Technical Success onboarding, role-based skill development, and ongoing readiness
• Redefine and operate the Subject Matter Expert (SME) program
• Create pathways for technical experts to share knowledge and increase technical depth and consistency across GTM
• Own and proactively maintain a versioned repository of technical pitches, demos, playbooks, and launch-ready assets
• Partner with Technical Success leadership, Product Enablement, and product SMEs to identify skill gaps
• Deliver targeted learning interventions
• Capture, vet, organize, and make field- and SME-generated technical content easy to discover, trust, and reuse

Field Enablement Lead, Technical Success

Data Scientist

• Build statistical and machine learning models to profile and improve GPU utilization, latency, throughput, and overall fleet efficiency
• Develop forecasting models for inference demand across products, regions, and model families
• Analyze production workloads to identify latency bottlenecks and capacity constraints, highlighting optimization opportunities
• Partner with Capacity Systems Engineering to inform infrastructure planning and long-term GPU investment strategies
• Design experiments and simulations to evaluate scheduling policies, serving strategies, and infrastructure tradeoffs
• Build dashboards and operational metrics that enable leadership to make data-driven capacity decisions
• Collaborate with Product, Research, Finance, and Infrastructure teams to align compute planning with business growth and model roadmaps
• Communicate technical findings clearly to engineering teams and executive leadership

Data Scientist, Inference Capacity Optimization

• Design, develop, and maintain software infrastructure for manufacturing process execution and data export
• Own integration across internal customers and vendor systems and processes
• Build and maintain CI, release, and delivery pipelines for tooling provided to external partners
• Build and maintain internal systems to ingest, process, deliver, and visualize critical data
• Build system health monitoring, telemetry, remote diagnostics, and recovery paths for manufacturing failures
• Develop automation frameworks and monitoring for board bring-up, rack bring-up, qualification, manufacturing readiness, deployment readiness, and long-term reliability
• Package engineering releases into manufacturing-ready software recipes, including images, versions, logs, limits, remediation mapping, provisioning hooks, secure artifact handling, and traceable data export
• Debug complex production issues spanning hardware, firmware, kernel, services, networking, power, thermals, boot, provisioning, manufacturing, test, and cloud services
• Partner with hardware, firmware, security, networking, infrastructure, manufacturing, operations, and external engineering teams to define software contracts, unblock bring-up, and resolve issues
• Produce architecture notes, runbooks, validation records, and decision documents to help OpenAI and partner teams reproduce, operate, and improve the platform
• Own system implementation, deployment, outputs, maintenance, and SLAs

Software Engineer, Manufacturing Infrastructure

General

• Own the stage-gate path from exclusivity and commercial terms through desktop diligence, confirmatory diligence, site closing, and handoff into design, construction, and operations
• Validate power pathways with Power and utility partners, including service options, interconnection and delivery sequencing, readiness assumptions, schedule exposure, cost implications, and decision points
• Turn each development phase into an action list with owners, deadlines, closure criteria, open evidence, and escalation paths
• Translate power, land, civil, environmental, access, entitlement, and permitting constraints into a building-level deployment plan
• Coordinate site access, exclusivity, LOI, commercial terms, financing assumptions, and closing requirements with partner teams
• Define desktop diligence scope, 15–30 day deliverables, and go/no-go criteria; govern the 90–120 day confirmatory diligence plan
• Set and track ECDs for easements, offsite improvements, well and pipeline locating, environmental studies, water-well testing, geotechnical reports, additional land, incentives, and other site-specific workstreams
• Scope and manage diligence vendors and consultants
• Maintain the integrated development schedule, budget implications, dependency tracker, risk register, mitigation plan, and executive escalation cadence
• Deliver executive-ready advance, defer, or stop recommendations and prepare the readiness package for transition into design, construction, and operations

Development Lead

• Lead high-stakes regulatory inquiries, investigations, and enforcement matters in the United States and internationally
• Develop strategy for contested enforcement proceedings and related litigation
• Coordinate across parallel matters and challenges to investigative demands
• Partner with litigation and subject-matter counsel on civil disputes involving privacy, consumer protection, class actions, cybersecurity, competition, copyright, trademark, and other IP issues
• Manage subpoenas, civil investigative demands, regulatory information requests, and discovery
• Prepare employees and executives for interviews, testimony, depositions, trials, and regulatory appearances
• Negotiate resolutions to demands, complaints, and enforcement matters
• Assess practical implications of proposed remedies and commitments
• Select and manage outside counsel, strategy, budgets, quality, timing, and outcomes
• Develop proactive and affirmative legal strategies addressing regulatory risk and responsible AI deployment
• Partner with Global Affairs and Communications on regulator engagement and sensitive external communications
• Assess emerging legal and regulatory developments affecting AI and advise leadership on risks, options, and next steps
• Work closely with Legal, Product, Research, Safety, Security, Communications, Global Affairs, and executive stakeholders

Senior Counsel, Litigation & Regulatory

Business Operations

• Design, build, and operate integrations across Oracle Fusion, Zip, and connected systems using APIs, events, messaging, and batch interfaces
• Build first-party procurement applications, backend services, and user-facing workflows for intake, approvals, transaction visibility, and exception resolution
• Write maintainable code and reusable integration components with version control, code review, automated tests, and repeatable deployment and rollback practices
• Define data contracts, mappings, durable identifiers, lifecycle states, and authoritative data ownership
• Engineer reliable processing through validation, idempotency, retries, monitoring, alerting, reconciliation, recovery, and system-of-record readback
• Build and evaluate AI-enabled workflows using OpenAI technology with scoped tool access, approval boundaries, audit trails, and safe error handling
• Make targeted Oracle Fusion and Zip configuration changes in partnership with Procurement, AP, and functional specialists
• Own technical testing and release readiness, including integration and regression tests, business UAT, migration validation, staged rollout, and operational documentation
• Own the procurement applications and integrations roadmap and make build-versus-configure decisions
• Own production health and incident resolution, protect access and financial controls, and reduce failed transactions, manual intervention, and procurement cycle time
• Partner with Procurement, Accounting, Tax, Legal, Security, Data, Engineering, AP, and Risk

Business Systems Lead – Procure-to-Pay

• Own integrated manufacturing and quality readiness for products across L6, L10, and L11, including gates, milestones, deliverables, owners, and closure criteria
• Lead readiness of process flows, tooling, fixtures, assembly operations, test interfaces, and production controls
• Review and contribute to work instructions
• Translate product requirements into qualification plans, process controls, test requirements, and acceptance criteria with design engineering and Area SMEs
• Coordinate product and process qualification, reliability testing, and validation with relevant SMEs
• Maintain traceable evidence that products and processes meet performance, reliability, and compliance requirements
• Own supplier and line scorecards using yield, defect tracking, process capability, and reliability data
• Identify trends and escapes, prioritize improvements, and verify effectiveness
• Lead containment, failure analysis, root cause investigations, and corrective actions during development, production, and deployment
• Drive corrective actions to closure with evidence that fixes are effective and sustained
• Work on-site with Area SMEs at supplier and sub-supplier locations to assess line readiness, troubleshoot issues, and verify controls and corrective actions
• Lead JDM/CM manufacturing and quality audits and performance reviews
• Assess manufacturing and quality impacts of design, process, source, and site changes
• Coordinate validation and control updates with engineering and sourcing owners
• Provide evidence-based release recommendations and clarify unmet criteria, risks, and remaining actions
• Manage multiple projects, track milestones, communicate priorities and risks, and coordinate mitigation to meet schedules and quality standards

Product Manufacturing, Quality Engineer

Manager

• Identify vulnerabilities emerging as models interact with tools, data, and external systems
• Translate vulnerabilities into model- and system-level safeguards
• Develop threat models and empirical frameworks for harmful outcomes from misaligned behavior
• Identify underlying behaviors and system conditions driving harmful outcomes
• Turn findings into policy frameworks, evaluation criteria, online measurement, and safeguards
• Develop human data campaigns and gold sets for measuring emerging behaviors and risks
• Partner with research, engineering, security, and product teams on model and system safety
• Balance trade-offs between safety, utility, and business risk
• Inform deployment decisions, system cards, safeguards reports, and OpenAI’s approach to agentic safety
• Build monitoring approaches to detect post-deployment regressions and emerging risks