Why this role stands out
As a Software Engineer on Glean's Agentic Runtime team, you'll contribute to a cutting-edge AI platform that's redefining enterprise knowledge, offering significant opportunities for technical growth and impact. This hybrid role is ideal for innovative engineers eager to shape the future of work within a rapidly growing, highly recognized company. Apply now to join a collaborative environment and build groundbreaking AI solutions.
Quick overview
Job description
- 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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