Generative AI Engineer with 2+ years of experience building enterprise AI solutions using Python, Gemini, Google Vertex AI, RAG, LangChain and LangGraph.
GenAI Engineer focused on building enterprise AI applications, assistants and agentic workflows.
I build Generative AI solutions using Python, Gemini, Google Vertex AI, RAG, LangChain and LangGraph, with a focus on retrieval, tool integration, vector databases, knowledge graphs and LLM orchestration.
My experience includes developing AI assistants for operational and incident use cases, RAG pipelines, LangGraph agentic workflows, FastAPI services and production-oriented AI deployments with Docker and CI/CD.
A practical stack covering GenAI, retrieval, backend engineering and deployment.
Hands-on AI systems spanning agents, RAG, semantic retrieval, APIs and deployment.
A production-ready Multi-Agent AI Trading Research Agent using LangGraph, RAG and LLMs to automate financial market research and report generation. The architecture combines Retriever, News, Sentiment, Risk, Summary and Memory agents with ChromaDB, Knowledge Graphs and multi-provider LLM support.
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.