Building LLM applications, RAG pipelines & agentic workflows — on a backend engineering foundation. Python · Django · LLMs · RAG · Document Intelligence
Associate Manager, Data Science at Tredence, focused on AI engineering — LLM applications, RAG pipelines, and agentic workflows. Behind that, 5+ years building scalable backend systems, APIs, and AI-powered workflow solutions with Python and Django.
I specialize in backend engineering, workflow automation, and LLM-enabled applications — including role-aware assistants, RAG-based workflows, and document intelligence systems.
Previously at GALE, where I contributed to enterprise products including Everest and LedgerAI — improving performance, modernizing legacy systems, and automating manual processes with AI.
The model is rarely the hard part. Retrieval quality, access control, orchestration, and evaluation are what decide whether GenAI makes it into production.
Enterprise products at GALE — publicly named on my profile.
Four mini-games. One built to work your memory.
Open to interesting problems in AI engineering — LLM applications, RAG, and the unglamorous parts that decide whether GenAI ships.