Track record. 5+ years of experience in infrastructure engineering, DevOps, or a similar role focused on building and operating large-scale, high-availability production systems at a high-growth product company.
Breadth. Experience running containerisation in production (a real cluster, not a lab), with experience in Helm and Terraform or Pulumi on at least one major cloud (AWS preferred), plus good proficiency in Python or Go for automation and tooling.
AI in workflow. AI is part of how you ship, not a thing you've read about — agentic tooling (Claude Code, Droid, Codex, internal skills) is in your daily loop, you've built or adopted AI-assisted workflows others now use, and you have strong opinions on where it's unreliable. This is a hard requirement, not a bonus. Candidates whose actual daily workflow does not already include AI tooling will not be advanced.
First-principles + decision-making. Demonstrated ability to Challenge the status quo, proactively identify systemic weaknesses, and propose innovative solutions to complex reliability problems — reason from constraints and failure modes (not analogy or vendor defaults), name the tradeoff in business terms (reliability vs. velocity, cost vs. blast radius, standardisation vs. one-off), and reject the "best practices" answer when it doesn't fit the problem.
Reversibility & blast-radius. Make reversible calls by default — write the rollback before you touch production, work fluently with monitoring and logging stacks (Prometheus, Grafana, ELK or equivalent), and stress the system in safe places so it comes back stronger.