12+ years total experience in software engineering, DevOps/platform engineering, SRE, security engineering, or solutions engineering, including 5+ years at lead, staff, or principal level with multi-team or enterprise-wide technical scope.
Forward-deployed or customer-facing engineering experience: embedding with teams, running discovery, shaping ambiguous problems into working solutions, and driving adoption with teams you do not manage.
Hands-on experience applying LLMs and agentic AI to software delivery and operations—AI-assisted development, code review, test generation, workflow automation, and AI-enabled operations—including prompt and context engineering, evaluation, and integration with enterprise APIs.
Strong DevSecOps and SDLC fluency: CI/CD, IaC and GitOps, automated testing, observability, incident and change management, and secure-by-design practices (static, dynamic, and dependency scanning, secrets management, SBOM).
Working knowledge of cloud-native architecture and AI infrastructure—containers, Kubernetes, managed cloud and AI services, model APIs and gateways, identity, and networking—sufficient to integrate, troubleshoot, and advise.
Experience designing security and governance controls for AI or data-sensitive systems in a regulated environment.
Ability to balance strategy and implementation: set direction at the portfolio level and personally build, debug, and ship.