Experience: Previous experience building developer tools and/or infrastructure for engineering teams
Technical Decision-Making: Expert ability to evaluate technical tradeoffs and understand how infrastructure decisions impact the daily productivity of the end-user (the developer)
Modern Tooling Proficiency: Fluent knowledge of industry-standard AI tooling, build tooling, containerization, and open-source development frameworks
Workflow Empathy: A demonstrated passion for building empathetic developer and operator workflows that prioritize human productivity
Cloud-Native Expertise: Professional experience managing or developing within Kubernetes clusters and a deep understanding of container orchestration
DevOps & Reliability Background: Proven experience in DevOps, Site Reliability Engineering (SRE), Release Engineering, or a similar productivity-focused discipline
Testing Infrastructure Knowledge: Deep understanding of automated testing infrastructure and how to integrate it into a seamless CI/CD pipeline
Language & Version Control Mastery: Expertise in modern programming languages (specifically Go) and advanced proficiency in Git-based workflows (GitLab/GitHub)
Mandatory Education: A Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related analytical field (or equivalent professional experience)
Strategic Vision: Experience informing long-term company objectives through technical insight and developer-centric advocacy
AI Platforms: Experience building AI agent platforms for engineering teams
Linux Internals: Hands-on experience with Linux image construction, package building, and kernel-level optimizations
Community Engagement: Active involvement in the open-source community or a track record of staying current with recent industry advancements in developer productivity
Automation Mindset: A background in solving complex, multi-layered technical problems and then successfully automating the resulting solutions