Product-Minded AWS Infrastructure Engineer
AWS Cloud Engineer · Cloud Infrastructure · DevOps · Platform Engineering

I build production-style AWS systems for real business workflows.

I design and deploy cloud infrastructure on AWS, choosing the right compute model, integration pattern, data layer, and deployment boundary for what the workload actually requires. My projects focus on secure cloud architecture, infrastructure automation, platform engineering, workflow automation, auditability, cost controls, and operational visibility.

The pinned repositories below are built to be inspected: public code, live demos where practical, Terraform, CI/CD, architecture docs, runbooks, security notes, cost reasoning, and known limitations.

• CloudOps and platform control planes with governed workflows, policy checks, audit trails, and operational visibility.
• Infrastructure automation tools for Terraform review, blast-radius analysis, approval gates, and release discipline.
• Production-style AWS applications using the right mix of serverless, containers, relational data, object storage, edge delivery, and monitoring.
• Kubernetes and GitOps platforms with tenant boundaries, deployment automation, observability, and teardown discipline.
• Business workflow systems that turn messy operational processes into structured APIs, dashboards, automation, and source-backed decision support.

Start with the operation.
Infrastructure is only valuable when it improves the workflow: safer releases, faster execution, clearer visibility, lower manual effort, better governance, and controlled cost.

Choose architecture from constraints.
I work backwards from the workload: bursty or steady-state, synchronous or asynchronous, private or public, single-tenant or multi-tenant, low-idle-cost or always-on, simple data store or relational model.

Make systems reviewable.
A good project should explain itself. I document architecture decisions, tradeoffs, security boundaries, cost posture, deployment shape, operational runbooks, and what is intentionally not built yet.

Use AI-assisted tooling responsibly.
I use AI tools to move faster, but I do not treat generated output as finished work. The final repo still needs architecture review, tests, CI validation, deployment evidence, security reasoning, and operational documentation.