Business analyst jobs in Seattle, WA

About the role

Guidacent is seeking a Principal DevOps Engineer experienced in AI daily use to improve individual and team work efforts. This is a senior individual-contributor role with significant influence: the right candidate will architect the delivery platform and developer experience (DevEx), define standards and reusable “paved roads,” make cross-team technical decisions, and mentor other engineers. We are looking for a strong DevOps practitioner first — someone deep in CI/CD, infrastructure-as-code, cloud, containers, and observability — who has folded AI tooling such as Claude or Cursor into their daily workflow and used it to make engineering standards and practices measurably better. Just as important, the right candidate knows how to be a careful, cost-aware user of these tools: getting real leverage from AI without token overuse. The role extends proven DevOps practice with AIOps and AI-assisted automation, and treats DevEx as a long-term, principal-owned concern. Formal people or team management is a welcome plus but not a requirement, but preference is for a hands-on principal-level IC and player-coach who wants to lead a team.

What you'll bring

• 8+ years in DevOps, platform engineering, or site reliability engineering, including a track record of senior technical ownership.
• Demonstrated experience architecting and setting direction for CI/CD and infrastructure platforms used across multiple teams.
• Strong CI/CD experience (e.g., GitHub Actions, GitLab CI, Jenkins, or Azure DevOps).
• Deep proficiency with infrastructure-as-code (Terraform, Pulumi, or CloudFormation) and at least one major cloud (AWS, Azure, or GCP).
• Hands-on containerization and orchestration with Docker and Kubernetes, including production-scale operations.
• Strong scripting and automation skills in Python, Bash, or Go.
• Experience defining observability and monitoring strategy (e.g., Prometheus, Grafana, Datadog, ELK).
• Regular, hands-on use of AI to make DevOps work more efficient — automating tasks, generating and reviewing code, troubleshooting, and improving tooling.
• Daily, hands-on use of AI coding tools (e.g., Claude, Cursor, or equivalent) as a core part of how they work — with a cost-conscious, token-aware approach rather than wasteful consumption.
• A demonstrated track record of using AI to make engineering standards and practices measurably better (e.g., better reviews, tests, automation, or paved-road tooling), not just to ship faster.
• Some level of AIOps experience — using AI-driven techniques for monitoring, anomaly detection, alerting, or automated remediation.
• Genuine interest in and ownership instinct for developer experience (DevEx) as a long-term concern.