Building Scalable RAG Systems, Agentic Workflows & Cloud Infrastructure
I am a Software Development Engineer, bridging the gap between distributed backend systems and production-grade Generative AI.
While many build AI demos, I focus on the infrastructure, scalability, and evaluation required to run AI in production. I combine deep backend expertise (Kubernetes, Microservices) with modern AI stacks (RAG, Vector DBs, Agents) to build reliable intelligent systems.
- 🔭 I’m currently building Production-grade RAG pipelines and Evaluating Agentic behaviors.
- 💡 I write about System Design & GenAI on Dev.to.
- 💬 Ask me about Python, RAG, Kubernetes, and Distributed Systems.
- 📫 Reach me at: sugamagrawal50@gmail.com
AI & Generative Engineering
Backend & Distributed Systems
DevOps & Infrastructure
| Project | Tech Stack | Description |
|---|---|---|
| RAG Evaluation Pipeline | Python LangChain Ragas |
A system to evaluate hallucination rates in LLM responses using Ragas and ground-truth datasets. |
| Scalable Vector Search | FastAPI Pinecone Docker |
High-performance microservice for semantic search over 1M+ embeddings with sub-100ms latency. |
| Agentic Workflow Engine | LangGraph OpenAI |
Autonomous agents capable of planning and executing multi-step backend tasks. |
Check my repositories for more backend and AI experiments.
