Portfolio
Major expertise
- Platform Engineering Leadership
  Full-lifecycle platform ownership across AWS, Terraform, CI/CD, observability, security and cost awareness, and the governance needed when teams depend on the platform.
- AI Platform Engineering and MLOps
  Agentic engineering workflows, evaluation gates, model and data lineage, deployment controls, and operational feedback loops.
- SRE-grade production systems
  Java, Rust, C++, Python, Go, and TypeScript where runtime behavior, interfaces, reliability, and maintainability matter more than framework fashion.
AI Platform Get in touch on LinkedIn Read the archive Publications CV About
Blog
AI Platform Engineering
Technical Archive and Platform Notes
- Archive essays
Latest Post
Agent-Ready Repositories
10 May 2026
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AI Platform
Current focus
AI maturity, agentic engineering, repository readiness, CI guardrails, and the platform operating model for safe delegation.
LinkedIn
Get in touch
Reach me on LinkedIn with the scope, constraints, and kind of platform work you want to discuss.
Publications
Talks and papers
Formal writing, seminars, and technical notes will live here as the archive is normalized into publication records.
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- Slides and handouts
Slides
Presentation material
A future home for talks on platform engineering, MLOps, infrastructure, typed systems, and applied software architecture.
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CV
Professional profile
A concise platform leadership CV will be added after the archive cutover and consulting pages are in place.
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About
Background
Engineering notes from the intersection of cloud platforms, AI infrastructure, data systems, and rigorous software design.
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Professional profile

CV

A downloadable CV will be added after the professional source material has been reviewed. For now, the public profile is intentionally concise: Platform Engineering Leadership across AWS, AI Platform Engineering, MLOps, Terraform, Kubernetes, data engineering, and production software.

Platform scope

Cloud foundations, infrastructure as code, CI/CD, observability, operational evidence, rollback paths, and governance for teams that depend on shared platforms.

Engineering scope

JVM services, TypeScript serverless systems, data pipelines, database boundaries, platform automation, and AI-assisted engineering workflows with reviewable controls.