Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

Leads national and locally tailored policy and brand marketing campaigns that build trust in OpenAI. Owns strategy, audience insights, creative development, paid media, stakeholder alignment, execution, optimization, and measurement. Translates complex AI policy and societal topics into accessible narratives for policymakers, civic leaders, communities, and the broader public. Partners cross-functionally with Global Affairs, Communications, Creative, Research, Product, and external agencies.

Build full-stack internal tools that improve the safety and reliability of AI models. Partner with researchers, engineers, and policy teams to support data labeling, failure-case analysis, model-policy workflows, and safety insight generation. Optimize applications for usability, performance, and scale, then help transform successful AI-assisted safety workflows into external safety products.

Lead technical accounting for complex compute infrastructure, investment, lease, power purchase, consolidation, and financial instrument arrangements under U.S. GAAP. Partner cross-functionally with Finance, Tax, Legal, Procurement, Infrastructure, and business teams; prepare auditor-ready technical memoranda; and translate conclusions into journal entries, close procedures, disclosures, controls, policies, and scalable processes.

Own the AMER higher education territory and strategic customer relationships, driving complex AI platform sales from pipeline creation through procurement, deployment, adoption, consumption, value realization, and expansion. Engage executive, academic, technical, security, legal, and procurement stakeholders; lead cross-functional pursuit teams; translate AI capabilities, governance, privacy, and security requirements into transformation roadmaps; forecast revenue and usage; and inform product and go-to-market strategy.

Manage relationships with venture capital funds, startup accelerators, and ecosystem partners to drive adoption of OpenAI models among startups. Develop portfolio engagement strategies, organize founder events, provide technical guidance, analyze startup metrics, gather product feedback, represent OpenAI publicly, and collaborate cross-functionally on customer programs and strategy.

Leads and grows infrastructure engineering teams responsible for highly reliable, large-scale production platforms. Oversees distributed systems, cluster reliability, scaling, rollout safety, SLOs, incident response, capacity planning, workflow orchestration, and storage foundations. Sets technical direction, partners with product and infrastructure teams, drives platform initiatives, and coaches engineers and emerging leaders across an ambiguous, rapidly scaling environment.

Drive technically complex AI research programs across model training, reasoning, evaluations, compute, infrastructure, safety, launch readiness, and governance. Translate evolving research priorities into actionable plans, navigate technical and operational tradeoffs, coordinate cross-functional stakeholders, assess experimental results and evidence, and keep ambiguous initiatives moving. The role requires hands-on engagement with researchers, engineers, technical systems, research data, and operational workflows.

Build and incubate differentiated executive and enterprise customer experiences for OpenAI. Define experience theses, prototype and test programs, lead cross-functional launches, evaluate commercial and customer outcomes, and determine whether initiatives should scale, remain bespoke, or stop. Create playbooks, operating requirements, and handoffs for successful pilots. The role is a senior individual-contributor position based in San Francisco with hybrid office requirements and possible travel.

Own and improve Bazel- and Yocto-based build systems, Buildkite CI pipelines, automated testing, remote caching and execution, and developer tooling for consumer-device software. Responsibilities include optimizing build and queue performance, reducing flaky tests, operating Kubernetes and containerized infrastructure, instrumenting CI observability, debugging distributed failures, applying AI to failure analysis, partnering with engineering teams, and participating in on-call support.

Design and lead fairness and bias evaluations for AI-assisted People systems across hiring, performance, promotion, development, and workforce planning. Conduct algorithmic audits, subgroup and intersectional analyses, validation studies, counterfactual and generative AI testing, and human-AI workflow evaluations. Build scalable testing, monitoring, documentation, and reporting infrastructure. Partner with engineering, People, legal, privacy, and security stakeholders to recommend mitigations and communicate evidence, risks, limitations, and uncertainty to senior leaders.