Jobs at Glean

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.

Design Engineer responsible for creating polished product experiences across web, desktop, and mobile applications. The role combines product design and frontend engineering, including design-system development, components, tokens, documentation, AI-ready design guidelines, motion, accessibility, prototyping, and code review. The engineer will partner closely with designers and engineers to establish a high standard of frontend craft and encode design expertise for AI coding agents.

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.

Partners with Account Executives to help enterprise customers across Latin America evaluate Glean’s AI and search platform. Leads technical discovery, solution design, tailored demonstrations, architecture workshops, proofs of value, technical evaluations, ROI cases, and executive presentations. Explains integrations, data flows, identity, permissions, security, and architecture tradeoffs while translating technical fit into business value. Requires collaboration with Product, Engineering, and Solutions Engineering teams, plus fluent Spanish and Portuguese and professional English.

Partner with enterprise customers across Latin America throughout the sales cycle. Lead technical discovery, solution design, tailored demonstrations, architecture workshops, proofs of value, technical evaluations, and business value development. Explain AI, search, SaaS architecture, integrations, identity, security, and operational tradeoffs to technical and executive audiences. Collaborate with Account Executives, Product, Engineering, and Solutions Engineering while delivering regional demos and customer insights.

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.

Drive new business and expansion within commercial and mid-market accounts by sourcing and closing net-new logos, building executive relationships, developing territories, responding to inbound leads, and running value-driven sales cycles. The role requires researching customer objectives, building champions, creating ROI cases, managing POCs, achieving ARR targets, and collaborating with internal teams to advance complex SaaS opportunities.

Build and maintain scalable full-stack applications, distributed systems, REST APIs, data ingestion pipelines, secure enterprise search indexing, and user interfaces. Responsibilities include code reviews, performance tuning on Linux, customer requirement analysis, and collaboration with product teams. The role requires machine learning and MLOps experience alongside Python, PyTorch, TensorFlow, NLP, AWS, anomaly detection, Scikit-learn, security, and data engineering expertise.

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.

Build scalable full-stack enterprise search and Work AI platform capabilities. Design and maintain front-end applications, REST APIs, application servers, backend systems, data pipelines, and distributed services. Develop user-facing features with TypeScript and React, server-side tooling with Node.js and Flask, and backend systems in Java and C++. Apply data analytics, visualization, and algorithm design to solve complex engineering problems and improve product decisions and system performance.

Build scalable, fault-tolerant distributed systems, data ingestion pipelines, secure enterprise search indexes, APIs, and user interfaces. Responsibilities include code reviews, performance tuning, customer requirement implementation, and collaboration with product teams. The role may involve cloud-native infrastructure, full-stack development, machine learning, or information retrieval systems using C++, Java, Python, Go, JavaScript, PyTorch, CI/CD, and GCP.

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.