Headline

Lead Data Scientist building Enterprise AI Systems

About

I build enterprise AI systems that combine applied AI, Gen AI, and operational intelligence to solve real business problems at scale. Over the last 9 years, I’ve worked across predictive analytics, NLP, RAG platforms, intelligent automation, and autonomous AI workflows , designing production-grade AI systems that improve decision-making, operational efficiency, and reliability across enterprise environments. My recent work has focused on: • autonomous AI and agentic workflows • RAG-based enterprise intelligence systems • NL2SQL and natural language decision platforms • predictive telemetry and operational intelligence • AI governance, evaluation, and observability I enjoy working at the intersection of AI systems, business decision intelligence, and scalable platform design, partnering closely with engineering, product, operations, and business teams to operationalize AI beyond experimentation into real world enterprise impact.

Location

Greater Bengaluru Area

AI stack

gemini

hugging face

langchain

langgraph

langsmith

openai

Work experience

Lead Data Scientist / AI Architect at Capgemini Invent, May 2025 - Present · 1 yr 4 mos, Bengaluru, Karnataka, India, Driving enterprise AI and GenAI initiatives focused on autonomous AI systems, operational intelligence, and scalable AI platform development across enterprise and industrial environments. Architected a production-grade autonomous AI testing platform using GPT-4o, LangGraph, Azure Functions, and agentic orchestration workflows to automate enterprise QA operations across web systems and physical devices. Designed scalable RAG-based NL2SQL systems integrating semantic retrieval, schema intelligence, evaluation frameworks, and LLMOps pipelines for enterprise decision intelligence and natural language analytics. Established AI governance, observability, and reliability frameworks including guardrails, HITL validation, evaluation pipelines, and runtime monitoring for production AI systems. Optimized AI orchestration, inference workflows, and retrieval pipelines to improve latency, scalability, and operational cost efficiency across enterprise AI ecosystems. Leading cross-functional AI initiatives spanning architecture strategy, production deployment, AI evaluation, and enterprise-scale adoption.

Technical Architect Data Science at Tata Consultancy Services, Sep 2022 - Apr 2025 · 2 yrs 8 mos, India, Led enterprise AI and predictive intelligence initiatives focused on operational analytics, NLP systems, telemetry intelligence, and scalable ML platforms supporting large-scale enterprise environments. Architected NLP-driven enterprise AI assistants using transformer models, semantic retrieval, and recommendation systems to automate IT support operations handling ~5K tickets/day. Designed predictive telemetry and device reliability systems across 50K+ enterprise endpoints using CatBoost, SHAP explainability, survival analysis, and scalable ML pipelines. Developed operational intelligence platforms enabling proactive diagnostics, failure prediction, lifecycle optimization, and deployment forecasting across enterprise infrastructure ecosystems. Built forecasting and decision intelligence frameworks using LSTM and statistical modeling techniques to optimize enterprise rollout planning and operational efficiency. Directed architecture strategy and AI delivery initiatives spanning predictive analytics, enterprise telemetry, intelligent automation, and production ML systems.

Machine Learning Engineer / Data Analyst at Bundle Technologies PVT LTD, Sep 2016 - Sep 2022 · 6 yrs 1 mo, Bengaluru, Karnataka, India, Worked on customer intelligence, personalization, and operational analytics initiatives using large-scale behavioral and transactional datasets within high-volume consumer platforms. Developed recommendation systems, churn prediction models, and customer intelligence frameworks to improve retention, engagement, and personalization. Built analytics pipelines and decision-support systems enabling operational optimization and data-driven business decision-making. Collaborated with product, analytics, and engineering teams to operationalize ML-driven insights across customer lifecycle and growth initiatives.

Education

Post Graduate Program, Artificial Intelligence and Machine Learning, Great learning

Bachelor’s Degree, Electrical and Electronics Engineering, N.B.K.R IST