I build production LLM systems — agents, RAG, and evaluation pipelines that hold up at scale.

Analyst — AI & Agent Systems · Jun 2026 – Present

Designing agentic memory architectures and building agent systems for operations and process intelligence.

AI and Fullstack Engineer · Jun 2025 – May 2026

Built ComplianceOS end-to-end: compliance automation workflows + agentic analysis over large regulatory corpora (DB → backend → cloud → LLM pipelines).

graph-rca

Log-to-resolution RAG system over 200 annotated production incidents — LLM parses raw logs into a causal DAG stored in MongoDB; ChromaDB (HNSW index) retrieves runbook context scoped to that graph traversal before generating a root-cause report. Output quality validated by a 3-model judge ensemble (Qwen3:32b, GPT-4o-mini, Llama-3.1-70B) across 9 reproducible experiment scripts; ships with CPU/GPU Docker Compose variants and one-command ./run.sh setup.

permission-mongo

RBAC-powered BaaS for MongoDB targeting 50K+ QPS custom AST-caching policy expression compiler, lock-free router with atomics, fasthttp tuned for 256K concurrent connections, batched async audit logging. Ships with labeled Prometheus histograms (latency, RBAC eval outcomes, cache hit/miss), a pre-built Grafana dashboard, and a Python SDK bundled alongside the Go service.

BetterBingImageDownloader

Published and actively maintained library with 18K+ downloads, 41 stars, 10 versioned releases; v3.0.0 was a correctness release fixing a thread-unsafe counter, atomic file writes, MD5 deduplication, and a global socket.setdefaulttimeout() side-effect. Test suite grew from 0 → 41 passing tests with GitHub Actions CI; follows full pip packaging lifecycle with pyproject.toml and entry-point CLI.