Jobs at Glean

Lead full-cycle recruiting for Forward Deployed and technical go-to-market roles. Partner with hiring managers on role definition, candidate profiles, interview planning, and priorities. Develop targeted sourcing strategies, analyze pipelines and funnel data, coordinate interviews, close candidates, promote inclusive hiring, and improve recruiting workflows using AI-enabled tools. The role is hybrid, requiring three to four days weekly in the Mountain View or San Francisco office.

Lead full-cycle technical recruiting for engineering, product, machine learning, infrastructure, security, data, and technical program management roles. Partner with hiring leaders on recruiting strategy, sourcing, assessment, candidate experience, market intelligence, and closing. Build talent pipelines, improve recruiting systems and processes, use data and AI tools to increase effectiveness, and mentor teammates while supporting scalable recruiting programs.

You will build a search and assistant product, improve personalization, train models, and write robust code while mentoring junior engineers.

Lead the Product Growth engineering function, setting technical direction and managing full-stack engineers building user-facing experiences that improve discovery, activation, engagement, retention, and adoption. Partner with Product, Design, Data Science, Marketing, and Applied AI; establish experimentation and measurement practices; contribute to architecture and code; own initiatives end to end; and hire, coach, and develop the team.

Manage day-to-day office operations, including supplies, food and beverage services, badging, employee events, facilities, vendors, equipment, laptop resets, budgets, expenses, and internal communications. The role ensures a clean, safe, welcoming, and productive onsite office environment while coordinating with employees, management, vendors, contractors, suppliers, and Finance.

Own Glean’s organic social strategy and content across LinkedIn, X, Instagram, TikTok, and YouTube. Create multimedia content, manage executive social accounts, lead live event coverage, scale employee advocacy, and develop technical social listening. Partner cross-functionally with Communications, PR, Product Marketing, Sales, and R&D while managing vendors, tracking performance, measuring pipeline influence, and protecting brand reputation.

Develop production machine learning systems for Glean’s Enterprise Brain, focusing on user understanding, task prediction, LLM workflows, personalization, reinforcement learning, ranking, and agentic systems. Build scalable evaluation and benchmarking loops, maintain ML pipelines and knowledge graphs, improve data and model quality, and collaborate cross-functionally to deliver reliable enterprise AI solutions.

Designs, builds, and operates resilient cloud infrastructure for reliable production services. Responsibilities include improving SLOs, automating deployments and operational tasks, managing incidents and on-call processes, optimizing performance and costs, implementing monitoring and alerting, supporting security and compliance, and advising on system architecture and software development.

The Product Manager for Growth will define and implement strategies for product growth, user activation, and retention across multiple platforms. They will collaborate with cross-functional teams to enhance user experiences and ensure the product meets customer needs while managing metrics and experiments to guide decision-making.

Define and drive the Enterprise Intelligence product strategy and roadmap. Conduct customer research, identify enterprise intelligence use cases, and build actionable workflows, dashboards, recommendations, and proactive experiences. Partner with engineering, design, data, go-to-market, and customer-facing teams to translate ambiguous concepts into detailed product experiences with clear user flows, quality standards, and measurable outcomes. Prioritize initiatives, support customer adoption, and establish product foundations for a new enterprise intelligence category.

Own the product strategy and roadmap for Glean Model Hub. Evaluate LLMs, manage model and inference-provider relationships, support customer experimentation, and oversee usage, cost, and capacity planning. Partner closely with customers and cross-functional teams to prioritize capabilities, enable adoption of new models, improve AI workflows, and build scalable processes. The role requires strong technical product management experience spanning enterprise SaaS, AI/ML operations, APIs, UX, and third-party partnerships.

The role involves defining and executing Glean's growth strategy through product management practices, focusing on activation, retention, and expansion by leveraging AI insights and cross-functional collaboration.

Build and ship fully native iOS and Android applications using Swift/SwiftUI and Kotlin/Jetpack Compose. Own mobile architecture, CI/CD, release infrastructure, enterprise authentication, managed-device support, security controls, OS integrations, and auditability. Deliver features including search, AI assistants, agents, notifications, widgets, and voice modes while ensuring accessibility, performance, offline behavior, and enterprise readiness. Establish AI-assisted development workflows and represent mobile in security reviews.

As a Product Manager at Glean, you will evaluate LLM models, define the product roadmap, manage relationships with providers, and drive customer adoption of AI capabilities.

Improve the quality and reliability of Glean’s AI assistants and agents through evaluation-driven development, model routing, retrieval, prompting, and post-training. Build supervised and preference-optimized models, reinforcement-learning environments, evalsets, LLM judges, and agentic verifiers. Analyze production traces, calibrate evaluation signals against human graders, balance quality with latency and cost, and partner with product, platform, research, and customer teams to ship production ML improvements.

Build data and evaluation systems for Glean’s AI products, including benchmark datasets, scalable eval infrastructure, agent observability, LLM-based verifiers, CI and production evaluation pipelines, and enterprise simulation environments. Analyze traces and failures, measure quality with statistical rigor, and translate findings into product improvements. Partner with research, engineering, product, and go-to-market teams to improve agent performance while balancing quality, latency, and cost.

Leads Glean’s global digital marketing strategy across paid media, search, web, email, social, retargeting, and emerging channels. Owns performance goals, reporting, budgets, agencies, conversion optimization, experimentation, SEO, and AI-driven discovery. Partners cross-functionally with sales and marketing teams to drive qualified engagement, pipeline, revenue, and efficient growth. Manages teams and develops account-based digital programs for an enterprise SaaS and AI platform.

Own Glean’s analyst relations program, including Gartner, Forrester, IDC, and other research firms. Lead major industry evaluations, manage briefings and inquiries, coordinate cross-functional submissions, prepare executives, oversee analyst subscriptions, support events, and track program outcomes. The role requires translating complex AI and enterprise technology capabilities into compelling narratives while building trusted analyst relationships and managing multiple deadline-driven initiatives.

Lead Glean’s enterprise security strategy and operating model across product, cloud, corporate, detection and response, risk, and compliance. Partner with Engineering, Product, Legal, IT, and executives to reduce risk, strengthen secure development, manage vulnerabilities, prepare for incidents, support audits and regulatory requirements, and secure AI-enabled systems. Build and lead multidisciplinary security teams while communicating risk, remediation progress, and business trade-offs to executives and customers.

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.