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

The role involves overseeing the development of cloud infrastructure, providing leadership, collaborating with teams, and writing efficient, maintainable code.

As a Software Engineer on Glean's Data Foundations team, you'll build and scale data ingestion connectors, transforming unstructured content into structured data while ensuring system reliability and security throughout the data processing pipeline.

The Regional Vice President leads a team of Strategic Account Executives, responsible for regional sales strategy, revenue targets, and customer success in complex enterprise sales cycles.

Drive new logo acquisition and expansion in the Bay Area by managing the full sales cycle, collaborating with internal partners, and delivering revenue targets.

Develop user-facing features and create frontend infrastructure using React.js and TypeScript, collaborating with product designers and backend engineers.

Design and build near production partner solutions on Glean, own end-to-end architecture, automate deployments with IaC, create reusable patterns and docs, advise strategic partners, lead workshops, enable partner teams, align technical plans with GTM, and collaborate across Sales, Product, and Engineering.

As a Product Manager, you'll own the development and success of AI agents, lead customer relationships, and shape product direction through collaboration with engineering and design teams.

As a Founding Forward Deployed Engineer, you will create AI solutions for clients, collaborate with teams, and manage deployments to solve business challenges, leveraging your technical expertise and client-facing skills.

Partner with executive sponsors and end users to identify high-impact AI use cases on Glean, define success metrics, run discovery and pilots, design AI agents and workflows, drive adoption and expansion, and advise on AI roadmaps while collaborating with product and engineering.

Partner with executive sponsors and end users to identify high‑impact AI use cases, run discovery and pilots, design AI agents and workflows, measure outcomes, drive adoption and expansion, and influence product priorities.