Engineer at the intersection of Chemistry and AI. Lead in practice. Senior on paper.
MSc Chemistry · MS Data Science · 6+ years production track at HTC — Chemistry data work that evolved into NLP, LLM extraction, and Agentic systems.
Chemistry taught me to distrust confidence without evidence. AI is still learning that lesson — and some of us are building the lessons in.
Half my work is building AI that behaves like a chemistry experiment — hypothesis, evidence, citation, peer review. The other half is refusing to skip the careful parts when everyone else is in a hurry.
Discipline isn't overhead. It's the work.
01 — Curie Citation-backed RAG pipeline for NMR structure elucidation. Retrieves first, reasons second, shows its work.
02 — Darwin AI-augmented technical interview platform. A 7-agent panel scores how candidates code with AI in the loop.
03 — SmartHire LLM-powered resume screening with structured candidate comparisons and SWOT analysis.
04 — Explore-AI A living notebook of AI topics. Published as I learn them.
Retrieve before you reason. Validate before you trust. Cite before you conclude.
Not a slogan — discipline. Chemistry fails publicly when you cut corners. AI fails confidently. Both demand the same humility: build the audit trail first, then earn the right to a conclusion.
I know it's hard. But it's possible.