Lead Site Reliability Engineer
Feb 2022 — PresentRemote
- › Built agentic AI skill framework with 17+ specialized skills for Claude Code and Cursor IDE integration, enabling automated code review, deployment orchestration, and infrastructure management — adopted cross-functionally across engineering teams
- › Developed parallel AI-powered PR review system spawning 4 concurrent agentic workflows (code quality, security, test coverage, architecture) to address review bottleneck from AI-accelerated code generation volume
- › Created multi-dimensional code analysis tool for GitHub Enterprise repositories with automated severity classification (critical/warning/suggestion) and optional AI-generated PR comment posting
- › Prototyped AI agent integration to automate 80-98% of engineering support requests, authoring PRD and proof-of-concept for automated ticket resolution across support channels
- › Built AI-powered work item management skill enabling natural language queries, CRUD operations, sprint detection, and automated report formatting on internal tracking systems
- › Shipped AI cost tracking and FinOps dashboard providing team visibility into LLM API consumption patterns and optimization opportunities across engineering tools
- › Established SLI/SLO dashboard standards with AI-calibrated thresholds using 60-day baseline data, replacing intuition with statistical analysis (P90, P95, mean+3σ) for monitoring alerts
- › Built interactive observability dashboards with one-click SLI drilldowns to root cause analysis, reducing MTTR for platform incidents across Terraform deployment pipelines
- › Fixed critical AWS GovCloud deployment failure in multi-environment sequential pipelines (EKS, Lambda, Step Functions) by implementing execution-aware dependency resolution, preventing false rejections in concurrent runs
- › Added pipeline failure classification metrics enabling differentiation between platform errors and service-team configuration issues, improving SLI accuracy from a noisy 42% error rate
- › Supported 300+ services in production deployment pipeline with 99% commercial and 33% government cloud adoption; implemented FedRAMP security controls across technical environments
- › Published reusable AI skill framework adopted across engineering teams; mentored engineers on prompt engineering best practices, agentic workflow design patterns, and AI integration with enterprise tooling (GitHub, AWS, Grafana)
- › Building fully autonomous AI agent platform using Mastra.ai to automate operational issue analysis, remediation, and support requests end-to-end — reducing headcount requirements and enabling 24/7 cross-timezone coverage with non-stop productivity
- › Led organization-wide migration to new GitHub Enterprise organization, enabling services to exit change moratorium constraints