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

Design, build, and operate Anthropic's managed caching platform: a scalable Redis fleet, client libraries, CDC-driven cache invalidation, multi-cloud deployments, observability, and tooling. Drive technical direction, optimize latency/hit rates/cost, partner with product and research teams, and make build-vs-buy decisions for caching infrastructure.

Lead cross-functional quote-to-cash programs end-to-end: own planning cadence, manage dependencies across CPQ/ERP/billing/provisioning, drive SOX readiness, coordinate engineering, finance, legal, and GTM teams, and deliver prioritized roadmap and status to leadership.

As part of the Data Science and Analytics team, the Data Scientist will drive data-informed decision making and improve developer productivity by analyzing metrics, conducting causal analyses, and presenting actionable insights to stakeholders.

Design and run RL experiments to improve code generation and autonomous coding; build environments, reward signals, verifiers, and scalable training pipelines; debug and own systems end-to-end; collaborate to deploy research into production while ensuring safety and correctness.

As a Startup Account Manager, you'll drive expansion and retention for high-growth startup customers, leveraging consultative sales expertise to enhance their AI capabilities and ensure maximum value from Anthropic's solutions.

Responsible for recruiting top talent for Core Tech teams, focusing on Machine Learning and AI. Collaborates with hiring managers to improve processes and enhance employer branding while scaling diverse teams.

As a Research Engineer, you will develop large scale ML systems, optimize infrastructure and enhance research tools while ensuring reliability and safety.

Manage operational health and progress of reliability infrastructure in AI systems, driving incident responses, maintaining service-level objectives, and coordinating platform projects.

Lead and grow an engineering team building investigation, review, and enforcement tooling and platform capabilities. Define roadmap for analytics, privacy-preserving data primitives, sandboxes, and automation that integrates Claude/LLMs into human-in-the-loop review workflows. Partner with policy, operations, legal, privacy, and data science to translate enforcement needs into reliable, privacy-compatible systems and hire and coach top technical talent.