Kumar Shubham

About Kumar Shubham

I build production-grade Agentic AI systems that combine modern backend engineering with large language models to solve real-world problems.I’m an AI Engineer specializing in designing and orchestrating multi-step LLM workflows, retrieval-augmented generation (RAG) pipelines, and scalable backend architectures using Python, FastAPI, PostgreSQL, React, and TypeScript.My work focuses on:• Designing and deploying Agentic AI systems using LangGraph and LangChain• Building RAG pipelines with vector databases and embedding architectures• Orchestrating multi-tool reasoning workflows in production environments• Developing high-performance REST APIs and scalable backend services• Implementing cloud-native deployments with Docker, Kubernetes, and Azure DevOpsI operate across the full development lifecycle — from architecture design and experimentation to CI/CD automation, deployment, and performance optimization.With a strong foundation in system design and backend engineering, I focus on building reliable, maintainable AI-native systems that move beyond prototypes and deliver measurable business value.Previously, I contributed to engineering teams at Wipro and LTIMindtree, where I built strong software fundamentals and delivery discipline.I’m particularly interested in AI platform engineering, applied LLM systems, and building scalable AI-driven products that integrate seamlessly into enterprise ecosystems.

Experience

1. Analyst

   Deloitte

   Dec 2023 — Present · Bengaluru, IN

   Designed and deployed Agentic AI systems, orchestrating multi-step LLM workflows using LangChain and LangGraph in production environments.• Built scalable backend services using FastAPI and PostgreSQL, supporting AI-driven application logic and real-time API interactions.• Implemented retrieval-augmented generation (RAG) pipelines with vector databases to enhance contextual reasoning and response accuracy.• Leveraged Databricks for data engineering workflows, AI experimentation, and ML lifecycle tracking using MLflow.• Developed responsive frontend applications using React and TypeScript, integrating AI-powered features into user-facing products.• Enabled cloud-native deployments via Docker, Kubernetes, and Azure DevOps, contributing to CI/CD automation and system reliability.• Collaborated in cross-functional Agile teams, contributing to system design, code reviews, and architectural decisions.

Education

• LNCT Group of Colleges

  Bachelor of Technology - BTech, CSE

  2019 — 2023