Charan Panthangi
Lead AI Engineer · Generative AI · Multi-Agent · RAG · MCP · LLM Evaluation · ML/DL · NLP · Transformers · GANs · Applied AI · IEEE Researcher · TechX Speaker
- Role
- Lead Engineer at Omnicom Media
- Location
- Bengaluru, KA, IN
- LinkedIn followers
- 500 followers
About Charan Panthangi
Lead AI Engineer with 7 years of experience building production-grade Generative AI, Machine Learning, and analytics systems across Retail, Finance, Marketing, Hi-Tech, and Industry 4.0.Currently at Omnicom Media Group (Fortune 500) as Lead Engineer — Generative AI & Product Development, where I architect multi-agent pipelines, RAG systems, MCP-standardised agent frameworks, and LLM evaluation infrastructure (GVAL) that governs 5+ active pipelines in production. I also serve on Omnicom’s internal GenAI research team, evaluating emerging AI technologies before enterprise adoption.Core expertise: RAG architecture · Model Context Protocol (MCP) · Multi-agent orchestration (Autogen, LangChain) · LLM evaluation & observability (OpenTelemetry, Maxim.ai) · Deep learning (CNN, LSTM, YOLO, BERT) · NLP · Vector stores (Weaviate, Pinecone, FAISS) · Python · FastAPI · DockerHighlights— 4 papers on applied AI in healthcare— Invited speaker, TechX Conference 2025 (Context Engineering & Agentic AI)— PGDM, IIM Indore · Quantum Computing, IIT Madras— 5 performance awards across Omnicom, BLP Industry.AI, and MphasisOpen to senior AI engineering, GenAI architecture, and ML leadership opportunities globally.
Experience
Lead Engineer
Aug 2025 — Present · Bengaluru, IN
Leading enterprise GenAI engineering at one of the world’s largest media groups — across multi-agent architecture, Model Context Protocol (MCP), LLM evaluation, and production observability.Designing and standardising MCP layers for structured agent-to-tool communication, context propagation, and memory handling across distributed LLM workflows. Orchestrating multi-agent systems with worker-agent flows, tool routing, and scalable execution using Autogen and LangChain.Built GVAL — a proprietary hybrid LLM evaluation framework combining NLI-based entailment, semantic similarity, LLM-as-judge validation, and distribution-level drift detection — governing 5+ active pipelines and automating evaluations per month via Maxim.ai.Engineered platform-level AI observability using OpenTelemetry (OTEL) — tracing agent runs, MCP calls, latency, and evaluation signals across all live deployments. Built golden-dataset regression pipelines and centralised dashboards for continuous LLM performance governance.Also part of Omnicom’s internal GenAI research evaluation team — reviewing, testing, and advising on emerging AI implementations before enterprise adoption. Annalectual of the Quarter · Rise & Shine Spot-on Award — 2025
Education
Jawaharlal Nehru Technological University, Anantapur
Bachelor of Technology - BTech, Mechanical Engineering
2014 — 2017
Saveetha School of Engineering
Master of Engineering - MEng, Applied AI, Applied ML,Gen AI, Nueral Networks, Research Methodology, Applied Statistics
Indian Institute of Management, Indore
Executive Program in Business Management, General Management and Contemporary Technologies
Sri Venkateswara University
High School Diploma, Mechanical Engineering
2010 — 2013
Indian Institute of Technology, Madras
Centre for Outreach and Digital Education, Quantum Computing
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