CTO • Software Architect • Systems Engineer
I build software systems from the infrastructure up — backend architecture, cloud platforms, security, observability, developer tooling, and increasingly AI systems.
I've spent 10+ years working across biotech, healthcare, fintech and security, usually around the difficult parts of software: architecture, reliability, complexity, and scaling teams and systems.
I care less about frameworks and more about understanding why a system behaves the way it does.
- 🤖 AI Engineering — agents, RAG, LLM applications, evaluation and AI-assisted development
- 🏗️ System Architecture — distributed systems, APIs, event-driven architectures and backend design
- ☁️ Platform Engineering — AWS, Terraform, Docker, CI/CD and developer experience
- 🔐 Security & Observability — audit logging, SIEM, threat modeling and production visibility
- 🔬 Reverse Engineering — understanding existing systems from the inside out
- 🛠️ Developer Tooling — tools that make engineers faster and systems easier to maintain
Led engineering for a DNA analysis platform processing large-scale genotyping data and generating personalized reports across 170+ traits.
Worked across the entire system — from laboratory data processing and backend services to infrastructure, ecommerce and customer-facing applications.
Redesigned AWS infrastructure using Terraform, reducing infrastructure costs by approximately 60–70% while simplifying the architecture and operational model.
Built audit logging, monitoring and observability systems designed to make production behavior visible instead of relying on assumptions and manual investigation.
Building and experimenting with RAG systems, AI agents and AI-assisted engineering workflows — with a focus on making them useful in real production environments rather than just demos.
I enjoy taking existing systems apart and understanding how they work — including low-level software, game engines and legacy systems.
- AI agents for software engineering
- Agentic workflows and multi-agent systems
- RAG architectures and evaluation
- AI-assisted code review and development
- Platform engineering and developer experience
- Observability for distributed systems
- Security-first architecture
- Reverse engineering and game technology
If a system cannot be understood, it cannot be maintained.
I generally optimize for:
- Clarity over cleverness
- Simplicity over unnecessary abstraction
- Ownership over dependency
- Observability over guessing
- Automation over repetitive work
- Understanding over blindly following conventions
I work primarily with:
Backend TypeScript · Node.js · Python · PostgreSQL · Redis · event-driven systems
Cloud & Infrastructure AWS · Terraform · Docker · CI/CD · Kubernetes
AI LLMs · embeddings · vector search · RAG · AI agents · evaluation
Security & Observability Audit logging · SIEM · monitoring · distributed tracing · threat modeling
I like working on things where the goal is simply to understand how they work.
That usually means reverse engineering, experimenting with game engines, building developer tools, or taking apart an old system just to see what happens.
I'm particularly interested in:
- complex backend and distributed systems
- AI systems that actually reach production
- infrastructure and platform engineering
- security and observability
- reverse engineering and low-level software
If you're building something interesting, feel free to reach out.