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

Lead and build product-facing features for a compensation platform: own projects end-to-end, collaborate with Product and Design, mentor engineers, break down ambiguous problems, and ship data‑intensive web applications using modern technologies.

Own daily IT operations for a distributed SaaS company: manage Google Workspace/Okta/Iru, identity and device lifecycle, AV and office systems, monitor security posture, lead one IT FTE and contractors, manage vendors and IT budget, support compliance (SOC 2/ISO 27001), and drive automation and integrations.

Lead complex enterprise sales cycles for Pave's compensation platform, selling six-figure deals to HR and Finance leaders. Build pipeline via inbound and outbound, partner with product, engineering, and customer success, influence roadmap, create account plans, and act as a trusted advisor to drive adoption and successful outcomes.

Lead design and delivery of Pave's AI compensation analyst: build production LLM-based agentic systems that reason over compensation data, implement retrieval and evaluation frameworks, drive 0→1 technical initiatives, and align engineering and product to ship autonomous AI features into production.

Partner with Marketing to analyze Pave's compensation dataset and produce published data stories, reports, and customer-facing data products; field data questions from stakeholders; build lightweight measurement frameworks; and translate complex findings into clear narratives that drive product and business impact.

Own and build foundational backend services, APIs, and data infrastructure (auth, data models, pipelines) powering the compensation platform. Design generalized platform solutions, lead large ambiguous cross-team projects, and deliver scalable, maintainable systems.

Lead Developer Platform initiatives to improve developer experience and velocity. Define CI/CD and observability standards, rethink local workflows and incident response, integrate AI-assisted/agentic tooling, partner across product and data teams, own developer velocity and reliability metrics, and scale production systems.

Build and maintain scalable data models and pipelines (especially Market Data) using dbt and Airflow; implement data observability, testing, and monitoring; collaborate with data scientists, product, and engineering to deliver production data products that drive revenue and customer value.

Build and own foundational services, APIs, and data infrastructure for Pave's compensation platform. Implement authentication/authorization, data pipelines, and models; drive large cross-team initiatives with a focus on scalability, maintainability, and product-led platform solutions.

Own full-cycle technical recruiting for R&D (Engineering, Product, Design, Data): source passive candidates, partner with hiring managers, manage interviews and offers, leverage Pave compensation data to close candidates, run pipeline reporting in Greenhouse/Gem, and use AI tools to scale sourcing and outreach.