Thelukuntla Sukesh Kumar

About Thelukuntla Sukesh Kumar

I’m an AI Engineer who loves building systems that think, reason, and act on their own. I’m deeply passionate about GenAI, autonomous multi‑agent workflows, and knowledge‑graph‑driven intelligence, and I enjoy solving problems that others consider complex or ambiguous.I specialize in turning ideas into production-ready AI solutions—from multi-agent pipelines and LLM toolchains to graph-based RAG, cloud-native workflows, and intelligent admin assistants. I’m driven by curiosity, a willingness to explore the unknown, and a strong belief that great AI systems should feel intuitive, reliable, and genuinely helpful.I’ve had the opportunity to work on impactful projects like autonomous lead discovery systems, agentic supply-chain intelligence, and Databricks platform automation—each one sharpening my ability to design scalable architectures, reason about systems, and collaborate across teams. I take pride in building solutions that improve decision-making, reduce manual effort, and deliver measurable business value.At my core, I’m someone who:enjoys breaking down complex problems into clean, structured solutionsthrives in fast-paced, innovation-heavy environmentsbrings a builder mindset—rapid prototyping → refining → scalingbelieves in continuous learning and staying ahead of the curve in AIIf you’re interested in GenAI, agentic automation, AI apps, or knowledge graphs, I’d love to connect and share ideas.

Experience

1. Program Analyst

   Cognizant

   Mar 2024 — Present

   At Cognizant, I design and build GenAI-driven, agentic, and autonomous AI systems that automate complex workflows, enhance decision-making, and reduce operational overhead across supply chain, data platforms, and B2B intelligence domains.Key Contributions & Achievements Autonomous Multi-Agent AI for B2B Lead DiscoveryBuilt a fully autonomous multi-agent system using Python, LangGraph, and LLMs to automate B2B lead discovery and enrichment.Integrated semantic search, web scraping, ICP scoring, and computer vision to analyze product images from e-commerce platforms.Created a stateful agent memory system to enable iterative querying, URL validation, and dynamic data resolution. Supply Chain Agentic System using CrewAI + Knowledge GraphsDeveloped an intelligent agent-based workflow that automates forecasting, PO planning, supplier scoring, and inventory reconciliation.Built a Neo4j knowledge graph RAG system integrating supply chain datasets for contextual reasoning and eliminating data silos.Implemented an LLM-driven Cypher query generator for natural-language-to-graph queries. LangGraph DBA – Intelligent Data Platform Admin ToolkitEngineered a Python-based toolkit that unifies workflows for job orchestration, metadata, lineage, cluster management, backups, and governance.Improved cost visibility and policy enforcement across data engineering teams. Databricks Admin AI AssistantBuilt a smart platform administration assistant using Python + Chainlit, enabling automated governance, security audits, and self-service ops for data teams.Automated ingestion workflows, warehouse cataloging, lineage tracking, and backup routines. Serverless AI Workflows (Azure)Designed a serverless lead-generation pipeline using Azure Functions, Cosmos DB, Key Vault, and modular agent tooling.Automated multi-step enrichment pipelines with scraping, validation, and LLM-based enhancement.

Education

• Vellore Institute of Technology

  Bachelor of Technology - BTech, Computer Science with IOT spl

• Sri Chaitanya College of Education

  12th , MPC

  2017 — 2019