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

Lead full-stack product development from concept through production, making key frontend and backend technical decisions and building scalable systems for large data volumes. Collaborate with research-focused colleagues, establish engineering standards, and mentor junior engineers while guiding technical direction during rapid company growth.

Manage and grow a software engineering organization developing AI-enabled products. Responsibilities include recruiting, mentoring, career development, technical leadership, architecture and design guidance, production troubleshooting, hands-on engineering support, and accelerating delivery through AI-assisted tools and agile development.

Own the front-end layer of a web application, working directly with users and leadership to translate feedback into interface improvements. Build and release intuitive multi-step workflows using React and Next.js, handle front-end and design tickets, define product solutions from ambiguous requests, and collaborate closely with engineers. The role is fully in-office in San Francisco and offers salary, equity, and comprehensive benefits.

Design, build, test, and refine electronic devices, including PCB layouts, sensor integrations, power systems, enclosures, embedded firmware, and microcontroller-based platforms. The role includes rapidly producing existing devices, improving fielded products, developing prototypes from concept through working hardware and firmware, and contributing to product direction. Hands-on soldering, wiring, assembly, and bench testing are central responsibilities.

Build and release customer-facing web interfaces, dashboards, analytics views, and configuration tools using React and TypeScript. Collaborate with backend and full-stack engineers, engage directly with customers during onboarding and troubleshooting, and turn feedback into usability improvements. Own frontend architecture decisions and deliver production-quality code in a fast-paced startup environment.

Lead high-value enterprise software sales from prospecting through contract execution. Qualify opportunities, build consensus among executive and technical stakeholders, run proofs of concept, coordinate with solutions engineering and product teams, and provide competitive and customer insights to leadership. The role requires winning $250K+ deals with long sales cycles, conversational AI or contact center technology experience, startup experience, and on-site work five days weekly.

Build coding evaluations and reinforcement learning task pipelines for coding-focused AI models. Run model evaluations against internal benchmarks, collaborate directly with customers to quality-check and deliver work, and develop reinforcement learning tasks. The role progresses from hands-on engineering to leading a small engineering team within approximately six months.

Investigate and evaluate potential securities litigation matters before filing. The attorney will analyze company reports, regulatory filings, market activity, and financial data; conduct public-record and source interviews; use AI and analytics tools; estimate damages; draft case materials; and collaborate with legal, financial, monitoring, and investigative teams. The role requires approximately five years of securities litigation experience, strong analytical judgment, and interest in plaintiff-side institutional investor work.

Build production features in Python and TypeScript for a specialized software platform. The role involves creating domain-specific content libraries, defining acceptance criteria, shaping product direction, reviewing automated design outputs, and supporting early external users. Candidates should combine professional software development experience with mechanical, electrical, or plumbing building-systems expertise. The position is fully on-site in San Francisco five days per week.

Design and build scalable evaluation systems for machine learning and LLM outputs. Define quality metrics, create labeled reference datasets, develop scoring pipelines, interpret statistical results, and connect findings to model and product decisions. The role requires strong Python skills, experience evaluating LLM-based data extraction or data quality, independent evaluation-system development, and comfort solving open-ended measurement problems. This is a full-time, on-site position in San Francisco or Toronto.