LLM pipelines with guardrails
JD Analyzer on this site is an LLM pipeline I run and maintain: structured extraction, scoring, evidence-cited risk flags, and a verdict, with evals checking the flags. At work I built a Gemini lead-enrichment pipeline with Google Search grounding, integrated an AI tutor into the learning platform, and built the backend AI voice agents run on.
Features shipped end to end
A live lesson whiteboard across a Laravel API, WebSocket broadcasting, the tutor app, and the student app. An IELTS writing-corrections workspace the same way. I take the feature, not the ticket.
Backends built from the first commit
The FastAPI control plane behind Dubtel's AI voice agents: tenants, a role hierarchy, SAML SSO, pricing with automated recurring invoicing,, and a managed Postgres migration. I built it solo.
Production is part of the job
I owned GitLab CI/CD and Docker deploys for Mango Capital and fixed what only breaks in production: exhausted DB connections, CORS with credentials, migrations that fight live containers.