I make AI systems reliable.

You're deploying agents and need them to work reliably across frameworks, environments, and scale. I design agent systems you can change, scale, and monitor without rebuilding from scratch.

• Swapped the entire storage and transport layer without breaking a single downstream integration: seven frameworks, zero regressions
• 2,000+ tests against latest framework releases, so integration breakage shows up in CI, not production
• Abstraction boundaries clean enough to swap SQLite for Postgres in an afternoon with zero application code changed

Your AI system is live and you have no idea what it's actually doing when it breaks. I build end-to-end observability using OpenTelemetry traces, Prometheus metrics, and Grafana dashboards so you can see exactly how your agents behave after deployment.

• Dashboards that show whether your agent is getting better or just more expensive
• Distributed tracing across every tool call: when something breaks, you see exactly which decision went wrong
• Drift detection that catches agent behavior changes before your users do

You're giving agents access to files, tools, or code execution and haven't threat-modeled it. I run STRIDE threat analysis, design containment architectures, and build sandboxing infrastructure to make autonomous agents safe to deploy.

• Found and patched an autonomous remote code execution path in an OpenAI foundation project: the kind of vulnerability that lets an agent run arbitrary code on your infrastructure
• Defense-in-depth sandbox that lets agents use tools without being able to reach your network, filesystem, or secrets
• Automated secret scanning that blocks agent output before credentials leak into logs or responses