Software Engineer, Compute Infrastructure

Other

• Design, build, and own backend/platform services that power Glean’s runtime infrastructure, with a focus on reliability, scalability, and performance for AI and search workloads. 
• Develop and evolve Kubernetes‑based runtime primitives (e.g., service orchestration, scheduling integrations, autoscaling patterns) across our multi‑cloud foundation (GCP, AWS, Azure). 
• Collaborate with platform, data, and product engineering teams to make it easy and safe to spin up new services and batch workloads, with clear golden paths for deployment, configuration, and runtime operations.
• Drive end‑to‑end improvements in latency, resource utilization, and cost for core platform services, including multitenant runtime environments and experimental AI workloads.
• Implement and harden infrastructure‑as‑code patterns, observability, and guardrails so teams can confidently ship and run services in production (e.g., SLOs, dashboards, alerts, safe rollout/rollback).
• Partner with the Costs and Runtime teams to build shared mechanisms for attribution, guardrails, and automation that keep our runtime layer efficient as we 5x customers and traffic.
• Participate in an on‑call rotation for critical platform services, lead incident response when needed, and translate learnings into better reliability, tooling, and documentation.
• Contribute to technical direction for Runtime Infra: help define roadmaps around multitenancy, autoscaling, capacity/placement, and platformized patterns that reduce per‑team hand‑holding.
• You are a backend/platform engineer who enjoys working close to the metal—where application behavior, infrastructure, and cost all intersect—and you are motivated by building shared systems that many teams depend on. 
• You have strong distributed systems fundamentals and experience operating high‑throughput, low‑latency services or batch pipelines in production environments.
• You are comfortable owning systems end‑to‑end: design, implementation, testing, deployment, observability, and ongoing operations. 
• You think in terms of reliability and guardrails: SLOs, incident response, safe deployment strategies, and clear operational runbooks are part of how you build.
• You are pragmatic and execution‑oriented: you can balance ideal architectures with the constraints of a fast‑moving startup and ship iterative improvements.
• You communicate clearly with both infra and product engineers, and you like collaborating across teams to understand requirements and translate them into platform capabilities.
• You are excited to work in a multi‑cloud, multi‑tenant environment and to help define best practices for running AI workloads efficiently at scale.
• This role is hybrid (4 days a week in our Mountain View office)