Posted:5 days ago
Build and operate enterprise DevOps solutions, with AKS and On-Premises Kubernetes as the primary deployment platforms. The role will also support EKS, Rancher-managed Kubernetes, Vanilla Kubernetes, and Air-Gapped (No Internet Zone) environments, focusing on CI/CD implementation, infrastructure automation, application deployment, monitoring, troubleshooting, and production operations. Must-Have Responsibilities Build and maintain CI/CD pipelines using Jenkins and Azure DevOps. Manage build artefacts, container images, dependencies, and release packages using JFrog Artifactory. Deploy, manage, and troubleshoot applications on AKS, On-Premises Kubernetes, Rancher-managed Kubernetes, Vanilla Kubernetes, and EKS. Provision and maintain infrastructure using Terraform. Build deployment pipelines for Python services, FastAPI/Flask APIs, microservices, React applications, and ML model deployment workflows. Containerise applications using Docker and deploy them using Helm and Kubernetes. Support deployment, monitoring, and operational management of ML models and AI services deployed on Kubernetes environments. Support software packaging, dependency management, artefact transfer, and deployment activities in On-Premises and Air-Gapped environments. Implement monitoring, logging, ing, and operational dashboards using Prometheus, Grafana, Splunk, or OpenSearch. Support application onboarding, deployment automation, release execution, rollbacks, and production deployments. Troubleshoot CI/CD, Kubernetes, networking, infrastructure, application, and deployment-related issues. Implement RBAC, secrets management, container security, vulnerability remediation, and operational security practices. Develop automation scripts using Python, Bash, Shell, or PowerShell. Create and maintain deployment documentation, troubleshooting guides, runbooks, and operational procedures. Participate in incident resolution, root-cause analysis, platform maintenance, and reliability improvements. Good-to-Have Responsibilities Support deployment and operation of HPC clusters for AI/ML, scientific computing, simulation, and distributed workloads. Assist with Slurm installation, queue management, job scheduling, and workload troubleshooting. Support GPU-enabled infrastructure and GPU workload deployments. Work with high-performance storage and distributed computing environments. Support Databricks and MLflow platforms. Assist with ML model serving and inference platforms. Exposure to LLM, RAG, and AI Agent deployment architectures. Assist with Rancher-based multi-cluster Kubernetes administration. Contribute to SRE practices, performance optimisation, and reliability improvements. Support reusable deployment templates, automation frameworks, and developer self-service capabilities. Evaluate and adopt modern cloud-native, DevOps, AI infrastructure, and HPC technologies.
React, Python, FastAPI, Azure DevOps
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