This page focuses on scope, decisions, complexity and impact rather than lists of responsibilities. For a traditional chronological history, see the full curriculum.

Current role: DevOps & SRE Manager

Since 2021

Scope. I lead the DevOps and SRE function: planning and priorities, alignment between engineering and business teams, high-level technical reviews, and mentoring the people on the team.

Decisions. What the team builds, what it standardizes and how its roadmap supports broader business objectives.

Selected work

Building an incident-management practice and an SRE team

  • Scope: built the process and the team from scratch and rolled it out across the technical teams over several months.
  • Decisions: selected the incident tool, defined technical patterns and automation, and set the SRE team’s mission and vision.
  • Complexity: adoption had to happen across many teams, so training and knowledge transfer mattered as much as the tooling.
  • Impact: a common process for incidents, and consistent postmortems and follow-up actions for major incidents.

An infrastructure-as-code lifecycle

  • Scope: a framework that lets teams operate infrastructure as code through a clear development lifecycle, reused across many Terraform modules.
  • Decisions: explored tooling and defined shared terminology so teams could talk about infrastructure changes the same way.
  • Complexity: making a repeatable process fit many modules and teams without slowing delivery.
  • Impact: automated drift detection, versioning and releases, hands-off operation of critical production components, and an easier path to roll out security and compliance improvements.

A zero-downtime Kubernetes migration

  • Scope: coordinated and helped implement the move of cluster management from eksctl to Terraform, with Argo CD and a structured GitOps repository.
  • Decisions: how to change cluster management without interrupting services.
  • Complexity: zero downtime was a hard requirement.
  • Impact: a migration with no downtime, better observability, faster node startup, right-sized components and a more predictable way to roll out Kubernetes changes.

AI-assisted engineering workflows

  • Scope: led the team’s adoption of AI in how it works day to day.
  • Decisions: where AI helps most: ticket refinement, documentation of changes and pull request review, including scaffolding agents.
  • Impact: faster feedback and review cycles, and less review effort.

Earlier roles

  • Staff DevOps Engineer and tech lead: made technical decisions on projects, guided other DevOps engineers, negotiated schedules with other teams and planned the roadmap for CI/CD tooling and application environments.
  • DevOps Engineer: built CI/CD pipelines and automation, worked with software architects on practices and development processes, and helped collect delivery metrics such as MTTR and change failure rate.
  • Tech Lead and Cloud Engineer: ran infrastructure on AWS, helped migrate legacy applications to the cloud, kept infrastructure as code under version control and took part in the technology board that set architectural standards.
  • Support and development roles (2009–2019): administered a large warehouse management platform, supported development and operations teams, and worked on payment-system queues, ATM software and ERP and network servers.