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

Leads applied AI scientists and engineers while owning Glean’s AI evaluation strategy, roadmap, and platform. Builds scalable evaluation infrastructure, datasets, graders, dashboards, and production feedback loops for LLMs, retrieval systems, assistants, and agents. Establishes quality metrics, validates automated judges, integrates evaluations into CI and release processes, and connects results to product decisions. Coaches a high-performing team and partners cross-functionally to improve reliability, quality, latency, and cost.

Drive Product Operations for a high-growth SaaS organization by establishing operating rhythms, roadmap cadences, launch reviews, and feedback loops. Lead cross-functional programs, align R&D, go-to-market, and product marketing teams, convert customer feedback and product usage data into insights, and maintain clear documentation and communication. The role requires product analytics, qualitative research, Jira expertise, SQL familiarity, AI fluency, and strong program execution.

Develop and maintain A/B experimentation and evaluation platforms for Glean’s AI products. The role designs rigorous statistical methods, evaluates LLM capabilities across tasks such as summarization, reasoning, tool use, coding, and system design, and establishes best practices for metrics, benchmarking, and experimentation. Responsibilities include productionizing scalable tools, analyzing product data, defining KPIs and guardrails, and partnering with engineering, product data science, product management, and design teams.

Coordinate candidate interviews across time zones, manage scheduling changes and cancellations, update recruiting systems, and provide a welcoming onsite experience. Partner with recruiters, hiring managers, and candidates to support an efficient, organized hiring process.

Own Glean’s Core Experience product strategy and roadmap across Homepage, mobile, desktop, browser extension, SDK, app shell, navigation, notifications, and settings. Drive cohesive, polished user journeys while partnering with Search, Chat, engineering, design, data, growth, and customer-facing teams. Focus on engagement, activation, retention, experimentation, virality, and session depth through data-driven product decisions, detailed workflow design, and rapid execution.

Own go-to-market strategy for Glean Enterprise Context, translating AI and enterprise data technologies into positioning, launches, technical content, customer narratives, and field enablement. Partner with Product, Engineering, Research, Sales, Customer Success, and Communications to establish Glean as a technical leader in enterprise AI and drive adoption of connectors, search, Enterprise Graph, structured data, memory, and related platform capabilities.

Provide proactive and reactive technical support for designated enterprise customers. Troubleshoot complex issues using logs, stack traces, browser traces, APIs, cloud technologies, SSO, and networking. Maintain customer runbooks and knowledge articles, configure content sources, manage alerts, develop remediation plans, educate users, and coordinate cross-functional product and service improvements. The role includes customer meetings, documentation, security processes, screenings, training, equipment use, and extended on-call coverage.

Lead product marketing for Glean Agents by developing go-to-market strategies, positioning, messaging, campaigns, and customer-facing enablement. Partner cross-functionally with sales, marketing, product, and customer teams to increase product adoption, refine features, maintain competitive differentiation, and provide customer and market insights. The role requires strong B2B SaaS marketing experience, analytical thinking, communication skills, and the ability to execute in an ambiguous, fast-paced environment.

Lead the strategy, design, and evolution of Glean’s public APIs, SDKs, and MCP capabilities for developers, customers, and partners. Own the end-to-end developer experience, including authentication, onboarding, documentation, error handling, versioning, webhooks, and rate limiting. Build sample integrations, analyze developer feedback and support patterns, define adoption and usability metrics, establish API requirements, and collaborate with engineering and enterprise partners to deliver reliable platform products.

Own technical success for strategic partners by leading onboarding, workshops, enablement, production deployments, and scaled delivery. Build AI and agent-based solutions, integrations, connectors, prototypes, reference implementations, and reusable technical assets. Develop partner capabilities, support complex implementations, troubleshoot production systems, provide product feedback, and establish repeatable services practices. The role is hybrid in San Francisco with 25%–50% travel.