Nagesh Deshmukh

About Nagesh Deshmukh

With over 7+ years of experience, I specialize in designing and delivering scalable, production-grade AI and machine learning systems. I have strong expertise in machine learning frameworks like TensorFlow and modern AI toolchains to build efficient models and intelligent systems. My background includes developing end-to-end MLOps pipelines covering model development, deployment, monitoring, and lifecycle management.I am experienced in building Agentic AI solutions and LLM-powered systems to solve complex real-world business problems, along with designing end-to-end AI architectures that integrate ML models, LLMs, data pipelines, and agent-based systems. I am proficient in cloud platforms such as AWS, Google Cloud, and Azure for building scalable AI infrastructure, and have hands-on expertise in containerization and orchestration using Docker and Kubernetes for reliable deployments.I focus on building production-ready AI platforms with a strong emphasis on scalability, reliability, and performance.

Experience

1. Agentic Ai & Generative Ai Lead Engineer Mlops & Llmops Expert in Global Analytics Division

   Concentrix

   Mar 2024 — Present · Pune, IN

   Project 1 – Workforce Management AI Platform (Healthcare Staffing Optimization)Designed and developed an AI-driven workforce optimization platform to recommend optimal shift assignments for healthcare professionals, significantly improving staffing efficiency and reducing scheduling gaps. Built predictive machine learning models to estimate nurse shift acceptance probability using historical workforce, scheduling, and behavioral data.Architected a scalable end-to-end ML platform on AWS, covering data ingestion, feature engineering, model training, evaluation, and deployment. Implemented automated MLOps pipelines using Amazon SageMaker Pipelines for preprocessing, training, versioning, and continuous deployment. Designed distributed data processing and parallel training workflows to efficiently handle large-scale healthcare datasets.Deployed scalable inference using SageMaker Multi-Model Endpoints to optimize latency and infrastructure costsProject 2 – Contract AI Platform (Agentic AI System)Built an advanced Agentic AI platform enabling natural language querying of customer contract data, significantly reducing manual effort and improving data accessibility. Architected an end-to-end AI system integrating Amazon Aurora, large language models, and agent-based workflows for intelligent data retrieval and reasoning.Designed multi-step reasoning and agent orchestration using LangGraph to handle complex workflows and dynamic decision-making. Implemented intelligent query routing to identify relevant datasets and generate optimized database queries. Integrated Amazon Bedrock for LLM-powered reasoning, natural language understanding, and response generation.Developed an LLM-as-a-Judge validation layer to automatically evaluate response accuracy and reliability before delivering results to users. Built a scalable deployment architecture with automated workflows, ensuring high availability, performance, and enterprise-grade reliability.

Education

• Maharashtra State Board of Technical Education (MSBTE)

  Diploma of Education

• Savitribai Phule Pune University

  Bachelor's degree

  2016 — 2018