Building autonomous AI systems, RAG pipelines, and structured LLM workflows
from scratch in Python — deliberate framework usage, full architectural control.
I'm an AI Engineer who builds agentic AI systems in Python — using frameworks deliberately and purposefully, with full understanding of every architectural layer underneath.
My focus is on RAG pipelines, multi-agent workflows, and cost-aware AI design. I also have hands-on production experience building enterprise web applications during my full-stack engineering internship — shipping 3 apps, improving workflow efficiency by 30%, and rebuilding a complete system under live client requirements.
"I use frameworks deliberately — always understanding the layer beneath before I abstract it away."
Shipped Python applications spanning agentic AI, retrieval systems, and backend architecture
Rebuilt from a single-store ChromaDB prototype into a hybrid-search, multi-user system — upload PDFs or CSVs, ask questions, get cited answers.
6-agent autonomous research pipeline — Supervisor, Search, Scraper, Summarizer, Critic, Synthesizer — with complexity-based model routing and quota-aware fallback between Groq and Gemini.
Production-grade autonomous agent — 4-layer pipeline (cache → pattern router → RAG → LLM) routing roughly 80% of queries with 0 LLM calls. Per-session cost roughly $0.0005.
Third-generation finance system — dashboard for passive logging plus a conversational agent for active querying, both writing to the same SQLite store.
AI career planning app that analyzes a resume against a job description or URL — delivers full gap analysis, skill mapping, and personalized roadmap in under 5–8 minutes. Clean separation between parsing, analysis, and output generation with no hardcoded assumptions about resume or job format.
A local MCP server exposing 6 developer tools — file ops, Python execution, and JSON utilities — with human-in-the-loop confirmation built into any action that writes or runs code.
Multi-question parallel SQL execution using LangGraph's Send API for dynamic fan-out across schema analysis and execution nodes, with inline review before any query fires.
Hands-on skills across Python, agentic AI, and backend engineering — built and tested in real projects
Autonomous systems built from scratch
Modular Python CLI systems
Enterprise web applications
AI Engineer open to full-time roles and internships at AI-first startups — reach out if you're hiring or just want to talk shop.
Looking for entry-level AI Engineer, ML Engineer, or Python Developer roles at AI-first startups.
Get In TouchInterested in contributing to open source projects or technical partnerships.
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