OpenAI

LLM Engineer

• Act as the single-threaded owner for operational readiness across NPI and ramp, accountable for outcomes from early bring-up through sustained production
• Translate OpenAI’s infrastructure strategy and engineering objectives into clear operating plans, execution priorities, and decision frameworks
• Drive alignment across Engineering, Operations, Strategic Sourcing, Finance, Capacity Planning, and Executive stakeholders by framing tradeoffs, risks, and recommendations
• Proactively identify inflection points where decisions or investments are required to protect long-term scale, reliability, or cost targets
• Influence operational strategy with manufacturing partners by setting expectations on execution rigor, accountability, and continuous improvement
• Drive overall NPI build readiness, including material accountability, manufacturing and test readiness, product data availability, factory infrastructure, and qualification plans
• Lead transition activities from NPI to mass production, partnering closely with Sustaining Operations teams to ensure seamless ownership transfer
• Translate engineering requirements into actionable, factory-ready plans with tier-1 manufacturing and integration partners
• Lead cross-functional build and debug cadences; ensure issues are clearly owned, aggressively driven, and formally closed with root cause and prevention
• Drive factory and deployment ramp readiness, including throughput, site readiness, yield targets, quality controls, and reliability gates
• Own end-to-end risk management—identification, mitigation planning, escalation, and executive-level communication
• Surface systemic bottlenecks, inefficiencies, or failure modes; propose and implement durable solutions across process, tooling, and organizational interfaces
• Build, formalize, and scale repeatable operating mechanisms that enable predictable, high-velocity hardware development
• Define requirements for operational systems (e.g., PLM enablement), and partner with internal teams to implement, test, and operationalize them
• Establish clear scopes, roles, and responsibilities across internal teams and external partners to ensure clean execution boundaries
• Build strong, trust-based relationships with contract manufacturers, OEMs, and integrators—driving accountability, performance, and transparency
• Support onsite factory builds and field deployments as needed (domestic and international travel)

Supply Chain Operations Program Manager – AI Infrastructure

Account Executive

• Manage a focused set of key federal accounts, developing and executing comprehensive federal account plans
• Lead federal customers through their AI adoption journey, from consideration to successful deployment
• Partner with solutions and research engineering to build and execute complex government customer programs and projects
• Own and manage a federal consumption revenue target
• Oversee consumption revenue forecasting and reporting
• Analyze key federal account metrics and provide insights to internal and external stakeholders
• Closely monitor the federal landscape (agencies, policies, competitors, partners, etc.) to inform product roadmaps and corporate strategies
• Collaborate cross-functionally with solutions, marketing, communications, business operations, people operations, finance, product management, and engineering
• Support the recruitment and onboarding of federal-focused team members
• Foster the development of our company culture within the federal practice

Account Director – Federal Partnerships

DevOps Engineer

• Own the strategy and operating model of the AI Deployment Engineering team in Korea, ensuring alignment with company objectives and the evolving needs of our customers.
• Lead, build, and mentor a team of high-performing AI Deployment Engineers to deliver exceptional customer outcomes, as demonstrated by production customer applications and increased API adoption.
• Serve as the technical advocate for our customers, synthesizing their needs to develop the Research and Applied Product/Engineering roadmaps.
• Act as the primary technical escalation point during development, fostering trust and maintaining direct communication with executive-level stakeholders.
• Serve as an industry thought leader, championing the safe and innovative application of our technology across various sectors.

Manager, AI Deployment Engineering – Korea

Operations

• Own integrated resource planning across budget, headcount, and hiring priorities, developing clear investment and tradeoff recommendations for B2B Marketing leadership.
• Design and improve the operating system for B2B Marketing, including priority-setting, weekly business reviews, update intake, decision forums, project tracking, and executive communications.
• Define the metrics, reporting cadences, and leadership narratives that show how B2B Marketing is progressing against business goals.
• Serve as strategic surge capacity for new or high-priority B2B Marketing initiatives, stepping in to define the plan, stand up the operating model, and program-manage execution from 0 to 1.
• Identify operational gaps across planning, resourcing, reporting, and execution, then design practical systems that improve clarity, accountability, and decision-making as the team scales.

Strategy & Operations Lead, B2B Marketing

Infrastructure Engineer

• Lead the architecture, development, and operation of identity infrastructure that spans cloud platforms, internal systems, and critical engineering services.
• Design and evolve systems for authentication, authorization, access governance, auditability, and policy enforcement with a strong focus on reliability, scalability, and secure-by-default design.
• Build foundational infrastructure and platform capabilities that are broadly used across engineering, research, and security teams.
• Improve the reliability, observability, performance, and operational maturity of identity infrastructure that supports mission-critical systems and workflows.
• Lead ambiguous, high-impact technical initiatives across security, infrastructure, and engineering teams, driving alignment and execution across multiple stakeholders.
• Partner closely with engineers, researchers, and security teams to build scalable access patterns and infrastructure that enable rapid development while maintaining strong security boundaries and operational rigor.
• Raise the engineering bar through strong technical judgment, thoughtful system design, operational excellence, and long-term ownership of critical infrastructure.

Staff Software Engineer, Identity Infrastructure Engineering

Backend Engineer

• Design, build, and operate backend systems that capture and process critical product, usage, and customer signals across B2B and API surfaces
• Build reliable data pipelines and infrastructure that help translate raw signals into actionable insights, model evaluations, training datasets, and product improvements
• Work on high-traffic, low-latency services in constrained environments, including systems with strict privacy and data-handling requirements
• Collaborate closely with data science, research, product, and infrastructure partners to identify user pain points, measure system behavior, and improve product quality
• Help develop the system needed to support model and product feedback loops, including signal capture, evaluation datasets, classifiers, and analytical tooling
• Operate with high ownership in a small team where priorities may shift quickly and the work spans multiple engineering domains

Staff/Senior Staff Backend Engineer – B2B Flywheel

Data Engineer

• Design, build and manage our data pipelines, ensuring all user event data is seamlessly integrated into our data warehouse.
• Develop canonical datasets to track key product metrics including user growth, engagement, and revenue.
• Work collaboratively with various teams, including, Infrastructure, Data Science, Product, Marketing, Finance, and Research to understand their data needs and provide solutions.
• Implement robust and fault-tolerant systems for data ingestion and processing.
• Participate in data architecture and engineering decisions, bringing your strong experience and knowledge to bear.
• Ensure the security, integrity, and compliance of data according to industry and company standards.

Senior Data Engineer, Core Experimentation

General Counsel

• Be the go-to counsel and partner for several teams focused on frontier AI models and products.
• Identify and address product, regulatory, copyright, commerce, privacy, and other legal risks and mitigations, including for agentic, commerce, and multi-modal experiences.
• Develop strategies for handling legal issues in creative ways and build processes for scaling flexible solutions that address risk.
• Serve as an expert in AI legal matters and help propose and advance AI legal policy positions.

Senior Counsel, AI Product

Product Marketing

• Lead day-to-day execution of customer and advertiser risk reviews, KYC/KYB onboarding, sanctions screening, and enhanced due diligence workflows across global customer populations.
• Manage lifecycle risk operations from onboarding through monitoring, escalation, reassessment, and offboarding for customers, advertisers, and strategic counterparties.
• Oversee sanctions screening operations across both customer and supplier populations, including development of automated screening workflows, escalation management, adverse media review, and disposition governance.
• Build and operationalize scalable customer risk and sanctions screening procedures and governance frameworks aligned to OpenAI’s risk tolerance and evolving regulatory expectations.
• Partner closely with Legal, Security, Procurement, Finance, and GTM teams to integrate risk controls into onboarding and operational workflows.
• Lead integration and optimization efforts across systems such as Salesforce, Persona, screening providers, workflow automation tools, and internal platforms.
• Develop dashboards, metrics, SLAs, and reporting mechanisms to provide leadership visibility into customer risk operations and screening effectiveness.
• Support investigations and escalations involving sanctions concerns, suspicious activity, fraud indicators, regulatory inquiries, or customer misuse scenarios.
• Build repeatable operational playbooks for onboarding, sanctions screening, adverse media review, and escalation handling.
• Identify opportunities to automate workflows and improve operational scalability without compromising control effectiveness.
• Explore and deploy AI tools to enhance and streamline OpenAI’s trade compliance efforts.

Manager, Third-Party Risk Management – GTM

• Support the day-to-day administration and maintenance of Vertex and related indirect tax systems.
• Maintain tax determination logic, product mappings, jurisdiction rules, and exemption configurations across billing and invoicing systems.
• Support indirect tax flows across checkout, billing, ERP, and financial reporting systems.
• Monitor tax engine performance and troubleshoot tax calculation or integration issues across systems.
• Coordinate tax engine updates, patches, and configuration changes in partnership with internal teams and external vendors.
• Execute testing activities including regression, integration, and user acceptance testing for tax-related system changes.
• Support onboarding of new products, entities, and jurisdictions into existing tax processes and systems.
• Assist with reconciliation processes between tax engine outputs, billing systems, and ERP reporting.
• Maintain documentation, process flows, operational procedures, and system support playbooks for indirect tax operations.
• Partner with Financial Engineering, Product Engineering, and Finance Systems teams to support tax-related integrations and data requirements.
• Support indirect tax audits by assisting with transaction-level data gathering, reconciliations, and system documentation.
• Help identify process improvement opportunities to enhance automation, controls, and operational efficiency within indirect tax systems.

Indirect Tax Technology Manager

• Deeply understand problems faced by GTM teams and customers, and identify opportunities where AI systems can make buying and adopting our technology faster and more intuitive.
• Define and drive the product vision and roadmap for a portfolio of GTM AI systems
• Build AI-powered products that improve pipeline generation, seller productivity, account prioritization, routing, attribution, and GTM execution
• Translate GTM strategy and operational needs into scalable product capabilities, PRDs, success metrics, and engineering priorities
• Lead cross-functional execution across engineering, vendors, systems owners, and business stakeholders
• Improve the data foundations behind GTM systems, including entity resolution, enrichment, scoring, and data movement.
• Use experimentation, metrics, and customer feedback to measure impact on pipeline quality, conversion, sales efficiency, and revenue execution
• Drive adoption and change management for new GTM capabilities across distributed teams

GTM Growth Product Manager

• Manage a portfolio of customer accounts, developing and executing strategies for a comprehensive account plan
• Support your customer accounts from initial engagement to successful deployment, expansion, and through to renewal
• Develop new and existing accounts through pipeline generation, discovery, evaluation, and successful adoption
• Partner with solutions and research engineering to build and execute complex customer programs and projects
• Own a revenue target
• Manage revenue forecasts
• Analyze key account metrics to create reports and provide insights to internal and external stakeholders
• 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 – Digital Natives Growth

Manager

• Design and maintain model policies across safety-relevant domains, including dual-use, agentic, and emerging frontier-risk areas.
• Translate risk and harm models into clear behavioral specifications, evaluation criteria, grading guidance, and system-level safeguards.
• Define practical boundaries between beneficial uses of AI and assistance that could materially enable harm, exploitation, misuse, or unsafe outcomes.
• Build policy artifacts that support model training, evaluation, and deployment. Partner with safety researchers, engineers, product teams, and other stakeholders to operationalize policy into scalable model behavior and measurable safeguards.
• Use red-teaming results, deployment data, model failures, over-refusals, under-refusals, and ambiguous edge cases to improve policy and evaluation quality over time.
• Identify emerging capability areas where frontier AI systems could create new safety challenges or lower barriers to harm.
• Study real-world deployments to identify where model behavior succeeds, fails, or drifts from the intended safety posture.
• Combine longer-horizon safety research with hands-on launch and deployment work.
• Contribute to system cards, safety reports, policy documentation, launch reviews, and external communications on OpenAI's approach to model safety and risk mitigation.
• Design and run human data campaigns, including gold set construction, labeling guidance, calibration, adjudication, and eval coverage analysis, to ensure policies can be reliably measured and improved.

Model Policy Manager

Security Engineer

• Oversee the design and implementation of physical security features, including vehicle controls, physical barriers, secure doors, and man traps.
• Collaborate with architects and engineers to incorporate security measures during the design phase.
• Manage the deployment of CCTV, access control systems, alarms, and monitoring solutions.
• Work with IT and security teams to integrate physical security systems with network infrastructure.
• Manage the installation, and commissioning of technical security systems for assigned regions.
• Manage a PSIM (Physical Security Information Management) – fusing alarms, access control, and CCTV video for real-time security monitoring.
• Develop and implement security operations protocols for data center sites.
• Ensure regular maintenance, testing, and upgrades of security systems.
• Train and support on-site security teams in system operations and emergency procedures.
• Serve as the primary point of contact for all physical security technology matters during construction and operational phases within the region.
• Liaise with internal teams, external partners, and vendors to align security measures with organizational goals.
• Ensure compliance with industry standards and best practices for data center security.
• Conduct regular security audits and provide recommendations for continuous improvement.

Data Center Physical Security Regional Lead

Mechanical Engineer

• Serve as the physical design SME for semiconductor customer engagements, helping FDE teams understand backend implementation workflows, constraints, and opportunities
• Partner with FDEs during customer discovery and scoping to translate ambiguous pain points into clear solution hypotheses, success criteria, and technical plans
• Support customer-facing technical conversations as a trusted advisor, engaging credibly with technical leaders
• Help shape AI-assisted solutions across physical design workflows, including floorplanning, place and route, clocking, timing closure, congestion, power, physical verification, and signoff
• Guide feasibility and integration decisions across the entire chip design lifecycle: design, verification, and physical design
• Partner with FDEs and customer SMEs to curate evaluation datasets, golden tasks, rubrics, and acceptance criteria for physical design use cases, ensuring evals reflect real workflows and meaningful success metrics
• Build or guide lightweight prototypes, benchmarks, methodology experiments, and internal tools that validate opportunities and accelerate solution development
• Educate and mentor the broader FDE team on physical design concepts, implementation flows, EDA tooling, and key trade-offs so the org can engage customers with greater depth and confidence
• Surface repeated customer signal to Product and Research to help shape roadmap, model behavior, and platform capabilities for semiconductor use cases
• Progressively take on broader FDE responsibilities, including customer discovery, solution architecture, prototype development, production deployment, and ownership of technical workstreams.