Experience building agentic or LLM-powered internal tools
Experience with workflow orchestration systems such as Temporal
Experience working at the boundary between research and production engineering
Familiarity with performance optimization, scheduling, or resource allocation problems
Experience building lightweight product or developer-facing tools
Strong experience building or operating production systems with a focus on reliability, scalability, and maintainability
A systems mindset: you naturally think in terms of bottlenecks, failure modes, interfaces, resource usage, and long-term operability
Solid hands-on experience with cloud infrastructure, Linux, and infrastructure automation
Experience with Kubernetes and operating distributed workloads in production
Strong coding skills, ideally in Python or similar languages used for backend systems and tooling
Strong judgment around where automation adds leverage, and where human control and reliability matter most
Experience building internal platforms, developer tooling, or infrastructure abstractions used by other engineers
Comfort working in ambiguous environments and taking ownership of open-ended technical problems
A pragmatic approach: you care about solving the right problem well, not over-engineering