Tech Lead Manager, Agentic Runtime

Details

About Glean

Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles.

At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level.

If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust.

About the Role

The Tech Lead Manager of the Agentic Runtime team builds the low-latency, reliable, and secure foundation that powers Glean’s AI agents and assistant experiences at scale. You’ll design and operate core runtime services for multi-turn orchestration, tool calling, model routing, memory, streaming, and safety. You’ll work across distributed systems, production observability, and ML infra integrations to deliver an experience that feels instant, accurate, and trustworthy — while optimizing cost and reliability.

Responsibilities

• Own impactful runtime problems end-to-end — from architecture and design to production launch and ongoing reliability.
• Build and evolve core services for session lifecycle, streaming responses (e.g., gRPC/WebSockets), structured tool execution, memory/state, and policy/guardrails.
• Design for performance, correctness, and cost: reduce p50/p95 latency, improve tail behavior, and optimize token/tool budgets.
• Integrate with leading LLM providers (e.g., OpenAI, Anthropic, Google Gemini) and internal evaluation frameworks to improve quality and predictability.
• Harden the platform with fault isolation, retries, timeouts, circuit-breaking, backpressure, and graceful degradation.
• Instrument deep observability (tracing, metrics, logs) and create playbooks/SLOs for high availability and on-call excellence.
• Collaborate closely with product, quality, and application teams to prioritize the most impactful roadmap investments.

Requirements

• 8+ years of software engineering experience building production distributed systems or cloud-native applications.
• 1+ years of engineering management experience.
• BS/BA in Computer Science or related field, or equivalent practical experience.
• Strong coding skills in at least one of: Python, Go, Java, or C++, with a focus on reliability, performance, and tests.
• Product-minded: you prioritize customer impact, clear SLAs/SLOs, and pragmatic iteration.
• Ownership-driven with a positive, proactive attitude; comfortable leading projects or learning from battle-tested engineers.
• Experience operating services on Kubernetes and at least one major cloud (e.g., GCP, AWS, or Azure).
• Familiarity with event/streaming systems (e.g., Pub/Sub, Kafka), caching (e.g., Redis), and data stores for low-latency paths.
• Practical understanding of LLM/agents building blocks: tool/function calling, structured outputs, streaming, and model selection/routing.
• Strong observability and debugging skills: tracing (e.g., OpenTelemetry), metrics, dashboards, and production forensics.
• Background in one or more areas is a plus: policy/guardrails, multi-tenant isolation, rate-limiting, concurrency control, cost optimization.

Location

• This role is hybrid (4 days a week in either our Mountain View or San Francisco offices).

Compensation & Benefits

• The standard base salary range for this position is $250,000 - $300,000 annually.
• We offer a comprehensive benefits package including competitive compensation, Medical, Vision, and Dental coverage, generous time-off policy, and the opportunity to contribute to your 401k plan.
• Home office improvement stipend, as well as an annual education and wellness stipends.
• Regular events and healthy lunches daily.

AI-First Mindset at Glean

As part of the interview process, you'll complete a brief AI-focused exercise or discussion so we can understand how you think about, design, and use AI to drive impact in your role.