GenAI Engineer with 2+ years of experience building enterprise Generative AI solutions using Python, LLMs, RAG, LangChain and LangGraph.
GenAI Engineer focused on building enterprise AI applications, assistants and agentic workflows.
I build Generative AI solutions using Python, LLMs, RAG, LangChain and LangGraph, with a focus on retrieval, tool integration, vector databases and LLM orchestration.
My experience includes developing AI assistants for operational and incident use cases, RAG pipelines, agentic workflows, FastAPI services and production-oriented AI deployments.
A practical stack covering GenAI, retrieval, backend engineering and deployment.
Hands-on AI systems spanning agents, RAG, semantic retrieval, APIs and deployment.
A multi-agent AI system using LangGraph, RAG and LLMs to automate financial market research and report generation. The architecture combines Retriever, News, Sentiment, Risk, Summary and Memory agents.
LLM-powered resume intelligence and ranking engine for semantic resume-job matching, candidate evaluation, skill extraction and contextual feedback generation.
OCR-based NLP application that extracts text from image documents, processes the extracted content and generates automated sentiment-based insights using VADER.
Technical presentations, knowledge sharing, cross-functional collaboration, peer mentoring, stakeholder communication, active listening and problem-solving.
Electronics and Communication Engineering
Global Academy of Technology · Bengaluru, India
Open to conversations around GenAI engineering, LLM applications, RAG, agentic systems and AI product development.