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

Lead technical direction for a research data platform supporting ML researchers: build reusable platform components and end-to-end datasets, drive canonical schemas and pipelines, collaborate with researchers, lead multi-quarter projects, stay hands-on in code, and mentor engineers to raise technical quality and adoption.

Serve as a strategic Customer Success Manager for Systems Integrators, driving adoption of Claude products (API, Claude Code, Claude for Enterprise). Build executive relationships, optimize usage and expansion across consumption and seat-based models, develop change management and enablement programs, document ROI, and inform product and GTM strategy while managing lifecycle and scalable engagement playbooks.

Serve as strategic Customer Success Manager for Financial Services clients, driving adoption of Claude products (API, Claude Code, Claude Enterprise), monitoring usage, identifying optimizations and expansion opportunities, executing change management and enablement programs, documenting ROI and business outcomes, owning account success plans and QBRs, and developing scalable playbooks to maximize customer value and product impact.

Design and run rigorous research on recruiting funnels, selection and assessment validation, and interviewer calibration. Build metrics frameworks, analytics solutions, dashboards, and presentations to inform recruiting strategy and measure impact while ensuring ethical handling of candidate data.

Lead technical design and delivery of enterprise-facing AI products end-to-end. Partner with product, design, sales, and research to turn enterprise workflows into shipped features, set architecture and standards, mentor engineers, and build extensible integrations, plugins, and multi-step agents for organizational use.

Own vision, strategy, roadmap, and execution for research-driven AI products. Partner with research and engineering to productize models, identify high-potential use cases, synthesize user insights, and ship model capabilities that solve real-world problems.

The role involves owning the technical strategy for developer productivity, designing reliable distributed infrastructure, and leading complex developer infrastructure projects.

Design new information architectures for language models, refine their interaction with data, and develop evaluation sets to improve functionality.

Build and scale infrastructure and data pipelines for Safeguards ML research. Own training, evaluation, and scoring workflows, design researcher-facing tooling, ensure correctness and reliability, productionize high-value research workflows, and improve throughput, cost, and reliability of large-scale inference and scoring workloads while partnering with researchers.

Provide commercial legal support for AI safety, research, and go-to-market agreements. Draft, review, and negotiate enterprise and research contracts, build contract templates and playbooks, partner with Sales, Policy, Safeguards, and Research teams, identify and escalate legal risks, and stay current on AI-related legal developments.