Languages
Python and TypeScript carry most of my work, with JavaScript, Rust, and Java on the side.
Open to full-time roles
AI backend Engineer — LLM systems, multi-agent workflows, and Python backends
I work mostly on the backend of AI products — multi-agent orchestration, retrieval pipelines over knowledge graphs, and FastAPI services built to stay maintainable as they scale. Most recently I built a Graph-RAG knowledge engine and a multi-tenant chatbot platform at Zaito AI, and I care about clean architecture and getting the boring parts right.
A few things I have designed and shipped lately — products, open source, and one experiment that never quite became a product.
A LangGraph pipeline that runs several agents in parallel to plan, research, and write a report on a topic. Redis and Celery handle the job queue, SSE streams progress live, and E2B sandboxes any code the agents generate.
Several AI agents paper-trade perpetual futures independently. A pipeline derives technical indicators such as MACD and RSI and feeds them to the model as context before it places a trade, through the Lighter SDK.
Recruiters post a role and immediately get a ranked list of matching candidates. Built on RAG best practices — query rewriting and metadata filtering — to keep the matches accurate. Won second prize at the CodeConquer ’25 hackathon.
Where I have worked, what I owned, and what shipped because of it.
Backend Developer Intern
Backend Developer Intern
Backend Developer Intern · Core product
The tools I reach for most, grouped by what I actually use them for.
Python and TypeScript carry most of my work, with JavaScript, Rust, and Java on the side.
LangGraph, LangChain, and PydanticAI for multi-agent systems, tool use, and typed agent flows.
Graph-RAG and vector search across Qdrant and Neo4j, including large-scale re-embedding migrations.
FastAPI, Express, and Node.js behind REST and WebSocket APIs, with a bias toward clean architecture.
Redis, Celery, and SSE for job queues and live progress streaming; Docker, Postgres, and Alembic for delivery.
Web scraping pipelines, third-party API integrations such as HubSpot, and onboarding messy data into knowledge bases.
Mysteries, mostly. Japanese detective fiction, locked-room puzzles, and one web novel that rewired how I think about worldbuilding.
Hover the shelf to stop it. 8 books, mostly detective fiction.
Open to full-time roles — in AI or backend engineering at an early-stage startup, or a project worth building together.