Product & Technology Strategy
Roadmaps grounded in architecture reality, with measurable outcomes and sane sequencing.
- Discovery to delivery ownership
- Build vs. buy decisions
- Technical due diligence
- Hiring and team design
Bridging product vision, cloud architecture, and high-concurrency engineering leadership.
12+ years of end-to-end software leadership, spanning distributed systems architecture (Python, Go, Cloud), product management execution, and agentic AI integration.
Services
Product direction, platform architecture, and delivery discipline — held by one owner instead of three.
Roadmaps grounded in architecture reality, with measurable outcomes and sane sequencing.
Distributed systems designed for throughput, clear boundaries, and graceful failure.
Agentic tooling and DevSecOps practices that shorten the path from idea to production.
Selected projects
Representative work adapted from real engagements. Full case studies are in progress.
A multi-tenant platform where Python and Go services meet over gRPC contracts. Built for high-throughput APIs, strict service boundaries, and predictable behavior under load, on Azure PostgreSQL.
A high-interactivity web engine with authoritative room state, low-latency sync, and a component-driven client.
Cloud security scanning wired into CI, automated container optimization, and Grafana monitoring that reaches the people on call.
Developer sandboxes, local LLM execution pipelines, and automated coding agent workflows that run autonomously without touching the host.
Experience
A generic summary of recent roles. Detailed history available on request.
Sitting across product and engineering, turning ambiguous business goals into resilient architectures, realistic roadmaps, and teams that ship without heroics.
Technical lead for high-concurrency backends, service decomposition, and the unglamorous reliability work that keeps platforms trustworthy.
Shipped cloud-native web applications end to end, with a focus on CI/CD, security scanning, and developer experience.
Company names and dates are intentionally omitted in this public version.
Writing
Field notes on distributed systems, AI agents, and the craft of shipping software.
The resilience patterns I reach for when a service absolutely cannot go down — and the trade-offs nobody mentions.
A grounded look at AI coding agents: where they help, where they hurt, and the guardrails that make them useful.
How to use gRPC and Protobuf so that service boundaries stay stable while the services behind them keep evolving.
Contact
Fractional CTO work, architecture reviews, or a stubborn distributed-systems problem — send a note.
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