About the Role
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. Glean is seeking a Software Engineer, Compute Infrastructure to help design, build, and operate the core compute and runtime platform that powers our AI search, assistant, and agentic workloads. Sitting within the Platforms organization, this role focuses on Kubernetes-based runtime systems, multi-cloud infrastructure, and cost‑efficient, low‑latency execution for production services and pipelines that serve our customers at scale.
Responsibilities
- 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.
Requirements
- 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.
Benefits
- The standard base salary range for this position is $140,000 - $220,000 annually. Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.
- 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 to support your long-term goals. When you join, you'll receive a home office improvement stipend, as well as an annual education and wellness stipends to support your growth and wellbeing. We foster a vibrant company culture through regular events, and provide healthy lunches daily to keep you fueled and focused.