Anirban Das

About Anirban Das

As a Global Lead Azure Cloud and AI Platform Architect at Kimberly-Clark, I bring over 23 years of IT industry experience ( 100% Individual Contributor) in designing and delivering data-driven solutions that enable digital transformation and business innovation. My expertise spans legacy modernization, data warehousing, streaming analytics, and AI/ML lifecycle management across multi-cloud environments.Innovative GenAI Solutions Architect with experience designing and deploying production-ready Generative AI solutions. Expertise in Retrieval-Augmented Generation (RAG) pipelines, LLM-powered chatbots, multi-agent AI workflows, and advanced LLM orchestration using LangChain and LangGraph. Adept at driving enterprise AI transformation initiatives, architecting scalable AI systems, and collaborating across cross-functional teams to deliver impactful business outcomes.I specialize in:Data & AI/ML Ops: Architecting scalable platforms for advanced analytics and machine learning.Cloud & Big Data: Azure, AWS, Databricks, Snowflake, Cloudera, MapR.Automation & DevOps: Azure DevOps, CI/CD pipelines, containerized deployments.Generative AI & OpenAI: Building enterprise-ready GenAI platforms for diverse business use cases.Core Competencies & Core Skills• AI Architecture & Strategy: Designing end-to-end GenAI solutions, aligning AI initiatives with enterprise goals, and leading AI transformation projects.• GenAI Solution Development: Building and deploying RAG pipelines, LLM-powered chatbots, and multi-agent workflows for real-world applications.• LLM Orchestration: Expert in LangChain and LangGraph for orchestrating complex LLM workflows and agent interactions.• Vector Databases: Hands-on experience with vector search technologies for efficient retrieval and semantic search in GenAI systems.• Cloud Platforms: Proficient in deploying AI solutions on major cloud platforms (Azure, AWS, GCP), leveraging cloud-native services for scalability and reliability.• MLOps: Implementing robust MLOps practices for model lifecycle management, CI/CD, monitoring, and governance.• Enterprise AI Transformation: Leading change management, adoption strategies, and governance for enterprise-wide AI initiatives.Technical Proficiencies• Programming Languages: Python, SQL• Frameworks & Libraries: LangChain, LangGraph, PyTorch, TensorFlow• Databases: Azure Vector DBs, SQL/NoSQL• DevOps/MLOps: Docker, Kubernetes, MLflow, Git, CI/CD pipelines• Other Tools: Power Platform, Microsoft Copilot, SharePoint Agents

Experience

1. Global Lead Cloud & Data Platform Architect-azure Gcp Aws,genai,ai Ml Ops,individual Contributor

   Kimberly-Clark

   Dec 2017 — Present · Atlanta, GA, US

   Key Responsibilities – 100% Individual Contributor, Azure Platform Engg & Operation for AI/ML platform with Generative AI & LLM Architecture implementation• Architect and deliver Generative AI solutions using LLMs, RAG architectures, and agentic AI frameworks within Azure Cloud• Build end to end GenAI pipelines for:• Retrieval Augmented Generation (RAG)• LLM based search and conversational AI• Autonomous agents and multi agent systems• Develop and optimize LLM orchestration workflows using LangChain, LangGraph, and similar frameworks• Design and scale enterprise retrieval systems, including:• Embeddings generation• Intelligent chunking strategies• Vector indexing and semantic search• Reranking for accuracy and relevance• Lead prompt engineering, prompt optimization, evaluation, benchmarking, and LLM fine tuning• Integrate LLMs and GenAI APIs into enterprise applications using microservices and APIs• Implement GenAIOps / LLMOps / MLOps practices, including CI/CD, monitoring, guardrails, and continuous improvementGenerative AI & LLM Expertise• Strong hands on experience with Generative AI and Large Language Models (LLMs)• Experience working with OpenAI GPT 4o,Llama, and open source LLMs• Deep understanding of RAG architecture, LLM based summarization, search, and content generation• Expertise in prompt engineering, prompt tuning, and LLM optimizationAgentic AI & Orchestration• Experience creating tool calling agents, autonomous agents, and multi agent workflows• Experience with vector databases and semantic search platforms, Azure AI Search• Experience deploying GenAI solutions on Azure cloud platforms:• Experience with LLMOps / GenAIOps pipelines• Knowledge of CI/CD for LLM workflows, evaluation frameworks, monitoring, and AI safety layersCollaboration & Leadership• Ability to collaborate across AI research, ML engineering, data, product, and business teams• Experience influencing AI strategy and architecture in enterprise environments

Education

• International Institute Of Management Science

  Master of Business Administration - MBA, Information Technology

• University of Geneva

  Doctor of Business Administration

• Great Lakes Institute of Management

  Postgraduate Degree, Data science

  2020

• The University of Texas at Austin

  Post Graduate in Artificial Intelligence & Machine Learning, AI/ML

  2020

• Jadavpur University

  Bachelor of Elec. Engineering - BE

• Indian Institute of Technology, Kharagpur

  Masters