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

Leads and develops a team of Applied AI Engineers driving Codex adoption for strategic customers. Oversees technical engagement strategy, AI-enabled development workflows, agentic systems, evaluations, architectures, and implementation challenges. Partners with Sales, Product, Research, and Engineering to translate customer needs into product insights and reusable technical patterns. Serves as a senior technical advisor, coaches engineers, establishes operating models and best practices, and champions safe, reliable AI adoption.

Lead the Solutions Architecture team, managing complex implementations of AI solutions, mentoring technical staff, and aligning customer needs with product roadmaps.

Build scalable data models, pipelines, metrics, dashboards, analytical tools, and self-service data products for Go-to-Market teams. Partner with stakeholders to solve ambiguous business problems, establish data strategies, operationalize trusted metrics, and communicate insights through persuasive narratives. Own data products from exploration through production and maintenance, balancing immediate needs with long-term scalability while applying strong analytics engineering practices and AI-assisted development tools.

Develop and maintain operating system foundations across kernels, userspace services, daemons, security mechanisms, performance and power systems, debugging tools, and application-facing APIs. Build secure, privacy-preserving, reliable platform software; diagnose kernel and userspace failures; support graphics, input, lifecycle, and update systems; and improve testing, observability, release readiness, and production hardening in collaboration with hardware, embedded, firmware, application, and product teams.

Own joint go-to-market and co-marketing programs across strategic technology partners and ISVs. Develop ecosystem messaging, launches, campaigns, customer stories, events, enablement, and demand generation. Prioritize partner investments, coordinate cross-functional stakeholders, and measure pipeline, revenue, adoption, engagement, and partner health. This individual contributor role requires influencing internal and external teams, simplifying complex technical concepts, and operating effectively in ambiguous, fast-moving environments.

Design and maintain Workday integrations and applications for critical HR workflows. Collaborate with teams to improve reliability, scalability, and performance of People systems.

Lead the systems integration organization responsible for device validation infrastructure, test automation, developer tooling, and lab operations. Define validation strategy, release criteria, quality metrics, and escalation processes across hardware, software, firmware, and reliability teams. Build scalable testing platforms, hardware-in-the-loop systems, device orchestration, diagnostics, and developer tools while managing device fleets, test labs, vendors, and operational capacity. Hire and develop engineering and lab operations teams and establish roadmaps that support products from prototype through launch.

Build low-level device runtime software for OpenAI custom AI accelerators. Responsibilities include kernel scheduling, command submission, queueing, device memory management, synchronization, hardware-software interfaces, simulation-based validation, performance tuning, debugging, testing, tracing, and profiling. Collaborate with compiler, kernel, architecture, verification, firmware, and silicon teams to improve accelerator execution and co-design.

Develop software bringup and validation strategies for new AI silicon and integrated systems. Build diagnostics, automation, telemetry, regression infrastructure, and stress tests across compute, memory, interconnect, and I/O subsystems. Lead first-silicon bringup through system integration and model execution, translate specifications into acceptance criteria, debug hardware-software issues, coordinate cross-functional fixes, and improve reusable infrastructure for future platforms.

Lead SMB Ads analytics end-to-end: define growth KPIs, diagnose funnel friction, build propensity/LTV models, design attribution and A/B experiments, automate dashboards, and forecast advertiser/revenue growth to inform product and marketing decisions.