Top Tech Jobs & Startup Jobs

Own Support Operations effectiveness through metrics, dashboards, AI-powered support tooling, automation, experimentation, and process improvement. The role manages support KPIs, operates AI agents and routing tools, partners with Product, Engineering, and Data Science on new use cases, leads cross-functional productivity initiatives, and develops workflows, documentation, runbooks, SLIs, and SLOs. The position is hybrid in Mountain View, requiring four office days weekly.

Build and launch user-facing backend features from inception through experimentation and ongoing improvement. Responsibilities include collaborating with product managers, designers, data scientists, and engineers; architecting scalable REST APIs; developing distributed CRUD systems using SQL and NoSQL technologies; writing maintainable, testable code; and mentoring or learning from other engineers.

Build Glean’s next-generation AI product surfaces from 0-to-1 in partnership with forward-deployed product managers and enterprise executives. Discover strategic customer problems, develop production AI-powered solutions, validate product hypotheses, and scale successful solutions with core engineering teams. The role requires full-stack software development, production AI experience, strong business and customer communication skills, independent judgment, and 25–50% travel. The position is hybrid in New York City.

Build Glean’s next-generation AI product surfaces as a founding Forward Deployed Engineer. Partner with customers, C-suite leaders, product managers, and engineering teams to identify business problems, develop production AI solutions, and create 0-to-1 products. Responsibilities include opportunity discovery, full-stack development, prompt and agent development, scaling successful solutions, and influencing Glean’s core platform. The role is hybrid in the San Francisco Bay Area and requires 25–50% travel.

Build Glean’s next-generation AI product surfaces from 0-to-1 in partnership with strategic enterprise customers and forward-deployed product managers. Identify high-value business problems, develop and ship production AI solutions, advise C-suite stakeholders, and scale successful prototypes with core engineering and product teams. The role requires strong full-stack technical depth, production AI experience, entrepreneurial judgment, customer communication skills, and 25–50% travel.

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.

Build and operate Glean’s agentic runtime, including orchestration, streaming, tool execution, memory, model routing, and safety services. The role focuses on distributed systems, low latency, fault tolerance, observability, cloud infrastructure, and production reliability. Responsibilities include integrating LLM providers, optimizing performance and costs, implementing safeguards, creating SLOs and operational playbooks, and collaborating across product and engineering teams.

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.

Lead the Admin Console engineering team and own architecture and execution for enterprise administration workflows, including authentication, data sources, permissions, governance, deployment management, and AI configuration. Partner with product, design, infrastructure, backend, connector, and security teams to improve usability, self-service activation, deployment visibility, and scalable enterprise control-plane capabilities. Mentor engineers and guide technical direction, roadmap, and execution.

Lead and grow the Admin Console engineering team while owning architecture and execution for enterprise workflows involving data sources, security, deployment, governance, permissions, and AI configuration. Partner with Product, Design, infrastructure, backend, connector, and security teams to simplify complex workflows, improve self-serve activation, increase deployment visibility, and build scalable control-plane capabilities for Glean customers.