I build production-grade AI systems β RAG pipelines, LLM agents, and async backends that work at scale.
Currently shipping Salesforce + cloud integrations at Codm Software while building AI infrastructure on the side.
focus = {
"building": ["RAG Pipelines", "LLM Agents", "Multi-Agent Systems"],
"stack": ["Python", "FastAPI", "LangGraph", "PostgreSQL", "Docker"],
"interests": ["LLM Optimization", "Vector Search", "MLOps"],
"open_to": "AI/ML Engineer roles"
}RAG-based document Q&A system with async processing and semantic search
- Multi-agent architecture with LangGraph for long-context workflows
- Async task pipeline via Celery + Redis β keeps API non-blocking under load
- Vector search with ChromaDB + pgvector for sub-second retrieval
- Fully containerized with Docker, CI/CD via GitHub Actions
PythonFastAPICeleryRedisLangGraphChromaDBDocker
End-to-end ETL pipeline that profiles Reddit users using NLP
- Extracts user data via Reddit API, stores in relational DB
- Text preprocessing and behavioral pattern analysis with Pandas + NLTK
- SQL-driven reporting on user persona traits
PythonPandasScikit-learnNLTKPostgreSQLETL
AI / ML
LLMs RAG LangGraph Prompt Engineering pgvector ChromaDB
Backend
Python FastAPI Celery Redis PostgreSQL SQLAlchemy REST APIs
DevOps & Cloud
Docker GitHub Actions AWS S3 CI/CD Render
- βοΈ AWS Academy Cloud Architecting β Jan 2025
- π€ Artificial Intelligence Foundations β SkillUp, Nov 2023
- π Foundations of Data Science β Google, Oct 2023
B.Tech in Computer Science (AI & ML) Β· Krishna Engineering College Β· 7.75 CGPA