Karan Sharma

About Karan Sharma

Passionate Senior AI Engineer and MLOps leader with 7.9 years of experience architecting and operationalizing enterprise-scale AI and machine learning platforms. Proven expertise in designing secure, production-grade infrastructures and end-to-end pipelines that bridge the gap between research and real-world applications. Skilled at driving GenAI adoption through cloud-native solutions, intelligent agent frameworks, and robust DevOps practices.Currently focused on building modern AI ecosystems with:Multi-turn AI Agent Architectures using Amazon Bedrock, LangChain, LangGraph, and custom agent collaboration modelsGenAI Platform Engineering leveraging AWS Bedrock, Azure AI Foundry, and native AI services (Kendra, SageMaker, Flow)MLOps pipelines: CI/CD automation, model registry (MLflow), monitoring, retraining loops, and A/B testing for AI modelsDeep Learning frameworks and LLM integration for NLP, Computer Vision, and Generative AI use casesContainer orchestration with Kubernetes/EKS, Docker, Helm, and scalable microservices for real-time inferenceInfrastructure-as-Code with Terraform, AWS CDK, and automated cloud governance for performance, cost, and security optimizationCross-functional leadership with Data Science, DevOps, Security, and Product teams to deliver AI-driven business impactKey achievements include delivering multi-agent conversational systems that improved query resolution by 30%, deploying LLM-powered pipelines serving 50K+ daily predictions, and reducing end-to-end ML deployment time by 60%. Experienced in AI ethics, bias mitigation, and scalable architecture design that supports full ML lifecycles from data ingestion to governance.

Experience

1. Senior Platform Engineer Mlops Genaiops

   bp

   Aug 2022 — Present · Pune, IN

   Architected and deployed multi-turn conversational AI agents using Amazon Bedrock, improving field technician query resolution by 30% through supervisor–collaborator agent hierarchies and AWS Flow for state management.2. Built enterprise intelligent search solutions with Amazon Kendra and Azure AI Search, achieving 85% search accuracy improvement and automating data ingestion from S3, SharePoint, and RDS.3. Developed and maintained scalable MLOps CI/CD pipelines using Terraform, AWS CDK, GitLab CI, and Kubernetes/EKS, enabling seamless model retraining loops and A/B testing for continuous performance optimization.4. Led cross-functional collaboration with Data Science, DevOps, Security, and Product teams to enforce AI governance, bias mitigation, and automated monitoring via CloudWatch and custom Lambda alerts.5. Integrated Chainlit and LangChain frameworks to deliver chat-based applications with session management and custom prompt engineering, accelerating GenAI adoption across business units.6. Implemented cloud governance policies and cost monitoring strategies, reducing AI platform spend by 25% while maintaining 99.9% SLA compliance.

Education

• JECRC University

  B.Tech, Computer Science Engineering

  2013 — 2017

• Springfield School

  ISC, Science with Maths

  2012 — 2013