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

As a Senior Software Engineer, you'll develop end-to-end systems, ensuring scalability and quality, collaborating closely with executives to align technical solutions with business goals.

Provide day-to-day legal support for a fast-paced tech company: draft and negotiate commercial contracts, advise cross-functional teams (revenue, product, HR, finance, engineering), assist corporate governance and board preparations, support public company readiness, oversee global corporate administration and compliance, and help scale the legal function.

The Customer Success Manager will drive account management and project execution, expand customer engagement, and ensure customer satisfaction while managing relationships and fostering partnerships.

The Senior Backend Software Engineer will own backend projects, design APIs, leverage AWS, and collaborate with teams to build financial products.

Lead and scale Poshmark’s product design organization, set design vision and strategy for buyer and seller experiences, drive AI-enabled design workflows, partner cross-functionally to deliver marketplace and social commerce features, and mentor design managers and individual contributors.

Lead the identity infrastructure and data connectivity strategy at Samba, collaborating with teams to enhance audience targeting and data interoperability.

Own the full enterprise sales cycle across the Southwest: prospect, demo, and close regional enterprise accounts. Build outbound motion, hit aggressive quota, collaborate with Sales Engineering, Channel, Product, and Customer Success to ensure smooth handoffs and long-term customer satisfaction.

The Product Marketing Lead will drive adoption of World ID by developing resources, educating stakeholders, and creating cohesive narratives that communicate product value effectively to various audiences.

Oversee the development of APIs and platforms for automated video editing, focusing on customer needs and collaboration with AI teams.

Lead ML engineering and infrastructure teams to design, build, and scale end-to-end ML systems (recommendation, personalization, ads), architect distributed low-latency serving and streaming platforms, oversee ML pipelines, ensure reliability, observability, cost efficiency, and partner with product and engineering to deliver ML-driven experiences.