Software Engineer, Agentic Runtime
- 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.
- 3+ years of software engineering experience building production distributed systems or cloud‑native applications.
- BS/BA in Computer Science or related field, or equivalent practical experience.
- Strong coding skills in at least one of: Python, Go, Java, Javascript, Typescript, 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.
- This role is hybrid (4 days a week in our Mountain View office)
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About the Company
About Glean:
Founded in 2019, Glean is an innovative AI-powered knowledge management platform designed to help organizations quickly find, organize, and share information across their teams. By integrating seamlessly with tools like Google Drive, Slack, and Microsoft Teams, Glean ensures employees can access the right knowledge at the right time, boosting productivity and collaboration. The company’s cutting-edge AI technology simplifies knowledge discovery, making it faster and more efficient for teams to leverage their collective intelligence.
Glean was born from Founder & CEO Arvind Jain’s deep understanding of the challenges employees face in finding and understanding information at work. Seeing firsthand how fragmented knowledge and sprawling SaaS tools made it difficult to stay productive, he set out to build a better way - an AI-powered enterprise search platform that helps people quickly and intuitively access the information they need. Since then, Glean has evolved into the leading Work AI platform, combining enterprise-grade search, an AI assistant, and powerful application- and agent-building capabilities to fundamentally redefine how employees work.
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