Chetan Nandwal

Experience

1. Machine Learning Engineer

   Genpact

   Oct 2024 — Present

   Architected and deployed production multi-agent automation frameworks using CrewAI, LangChain, and ChromaDB for autonomous incident resolution across database, network, and cloud infrastructure domains, reducing overall mean time to resolution (MTTR).• Database Incident Resolution: Designed end-to-end RAG-driven pipeline (SOP retrieval → Azure CLI remediation → diagnostics validation) to autonomously resolve database performance degradation, connectivity failures, and configuration issues. Implemented vector search using ChromaDB for intelligent SOP matching with 92% accuracy.• Network Incident Resolution: Built multi-agent workflows for on-premise and Azure network automation, handling switch/router failures, latency anomalies, routing disruptions, and Azure virtual network issues. Orchestrated agent coordination for complex multi-step remediation sequences with rollback capabilities.• AWS Infrastructure Automation: Engineered ServiceNow → GitHub Actions → Terraform pipeline for automated provisioning and deprovisioning of EC2, RDS, and S3 resources. Integrated CMDB updates, backup validation logic, resource cooldown periods, and secure termination workflows.• Production MLOps & Kubernetes Deployment: Deployed containerized multi-agent systems on Kubernetes clusters using Helm charts for environment management. Implemented Azure DevOps CI/CD pipelines with automated testing, Docker image builds, and progressive rollout strategies. Configured horizontal pod autoscaling (HPA) based on Redis queue depth metrics, enabling dynamic scaling from 4 to 10 pods under high load.• Containerized agent workloads using Docker for consistent deployment across dev, staging, and production environments.

Education

• SAE NIT Kurukshetra

  Master of Computer Applications

• National Institute of Technology Kurukshetra

  Master of Computer Applications - MCA

• DAV college Chandigarh

  BCA, html,c language,videos or snaps editing