Generative AI Engineer - RAG & Agentic Systems

ARUMUGAM R

GENERATIVE AI ENGINEER LLM & AGENTIC SYSTEMS RAG PIPELINES

Chennai, Tamil Nadu, India +91-812******* **************@*****.*** PROFESSIONAL SUMMARY

Generative AI Engineer with 6+ years of professional experience at SenseApp Technologies, focused on Python-based data pipelines, LLM applications, retrieval-augmented generation (RAG), and multi-agent workflows. Experience with LangChain, LangGraph, FAISS, Pinecone, FastAPI, and Streamlit. Built internal research automation and customer-support systems combining document retrieval, tool use, response validation, and API-driven interfaces.

TECHNICAL SKILLS

Languages & data: Python, SQL, Pandas, NumPy, REST APIs, JSON, Git GenAI & orchestration: OpenAI API (GPT-4), Claude, LangChain, LangGraph, LlamaIndex, multi-agent orchestration, prompt engineering, RAG, NLP

Retrieval & evaluation: FAISS, Pinecone, ChromaDB, Hugging Face embeddings, semantic search, vector search, LangSmith, model evaluation

App development & cloud: FastAPI, Streamlit, Gradio, Hugging Face, AWS S3, GitHub, Docker (basic), Jupyter Notebook PROFESSIONAL EXPERIENCE

GenAI Engineer SenseApp Technologies Jul 2020 – Present

• Built Python and SQL data pipelines to clean and structure source data for AI workflows, reporting 240+ hours of annual data- preparation time saved.

• Created 50+ reusable prompt templates covering system prompts and few-shot patterns to standardize LLM application development.

• Optimized SQL queries and retrieval workflows, reporting a 25% reduction in data access time for RAG context loading.

• Automated data validation using Pandas and NumPy to identify data quality issues before inference and evaluation.

• Analyzed user behavior and segmentation to inform model inputs and feature prioritization. Selected professional projects at SenseApp Technologies Multi-Agent AI Research & Automation System

• Built a LangGraph-orchestrated research system with researcher, summarizer, critic, and aggregation agents to delegate and synthesize complex tasks.

• Integrated Hugging Face embeddings, FAISS/Pinecone, web search, and API tools in a RAG pipeline for multi-source retrieval.

• Implemented shared agent context, similarity ranking, and a FastAPI/Streamlit interface for interactive research workflows.

• Developed citation-backed synthesis and evaluation workflows; resume reports approximately 50% fewer hallucinations. Customer Support Ticket Resolution Assistant

• Developed a multi-agent assistant for ticket classification, diagnosis, knowledge retrieval, escalation, and response drafting.

• Used LangGraph and RAG to retrieve troubleshooting steps from knowledge bases, FAQs, and support documentation.

• Added response checks against retrieved documentation and business rules; delivered a FastAPI backend and Streamlit front end. EDUCATION

B.Sc. Computer Science Annai Violet College 2015–2018 CERTIFICATIONS

Anthropic Prompt Engineering & Fundamentals (Claude) — Anthropic (2026) Deloitte Technology Job Simulation: Coding and Development — Deloitte (2025)

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