Aditya Katheeth
AI & Data Engineer · LLM Systems · ML Infrastructure · Applied AI Research
Production data systems by day. Researching how the systems we ship affect the people they decide about.
- 8+ years shipping production data infra at scale
- M.S. in AI · transitioning to AI engineering
- Fairness audits as a craft, not just a topic
Now
What I'm working on
Updated quarterly. The honest version.
- ▸Architecting agentic AI systems on Snowflake Cortex
- ▸Reading: Crawford's Atlas of AI; Barocas/Hardt/Narayanan
- ▸Building: an open-source fairness audit playground
- ▸Applying: doctoral programs in AI ethics
Featured Work
Three things I shipped
A sample of production AI/ML systems.
Snowflake Cortex Multi-Agent Platform
Multi-agent LLM system over enterprise data — natural-language querying across three business units, surfaced at VP level, with full auditability and access controls.
Real-Time NLP Sentiment + Market Intelligence
Production NLP pipeline combining customer sentiment with competitive intelligence — cut executive reporting from 2 weeks to 2 days (85% faster).
ML-Based Anomaly Detection on Snowflake
Continuous telemetry across thousands of daily query executions — surfacing model degradation, data integrity failures, and performance regressions before they propagated downstream.
Tools
Featured: Fairness Audit
Drop in a CSV. Get a fairness audit in under a minute.
Built so every ML engineer can run a basic disparate-impact check before shipping — not just researchers with aequitas notebooks open.
Writing
Recent essays
Engineering, ML, and the systems we ship.
Coming soon — drafts in flight.
Browse all writing →