Devops AI Engineer

DevOps Engineer – AI/Cloud(Manadtory)

Location: Remote – India

Experience: 3-7 Years

Employment Type: Full-time

About the Role

We are looking for a DevOps Engineer with strong experience in cloud infrastructure, Kubernetes, automation, CI/CD, and infrastructure-as-code. The ideal candidate will also have exposure to AI/ML or GenAI environments and will help build secure, scalable, and highly reliable infrastructure for modern AI-enabled applications.

Key Responsibilities

• Design, implement, and maintain scalable cloud infrastructure across AWS, Azure, or GCP.
• Manage containerized workloads using Docker and Kubernetes.
• Build and maintain CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, or similar tools.
• Automate infrastructure provisioning and configuration using Terraform.
• Manage Linux-based systems, networking, deployments, and troubleshooting.
• Develop scripting and automation using Python, Bash, or similar languages.
• Implement secure secrets management, access controls, and infrastructure security practices.
• Set up monitoring, logging, alerting, and observability for applications and infrastructure.
• Implement security and vulnerability scanning across containers, dependencies, code, and cloud infrastructure.
• Support deployment and infrastructure requirements for AI/ML, GenAI, LLM, or data-intensive applications.
• Collaborate with engineering, security, and AI/ML teams to improve reliability, scalability, and deployment velocity.

Must-Have Skills

• 3+ years of hands-on DevOps / Cloud Engineering experience.
• Strong experience with at least one cloud platform: AWS / Azure / GCP.
• Hands-on Kubernetes and Docker experience.
• Strong knowledge of Terraform / Infrastructure as Code.
• Experience with CI/CD using GitHub Actions, GitLab CI/CD, Jenkins, or equivalent.
• Experience supporting AI/ML, GenAI, LLM, RAG, or AI-agent workloads.
• Strong Linux administration and troubleshooting skills.
• Scripting experience in Python, Bash, or Shell.
• Experience with secrets management and cloud security practices.
• Exposure to observability, monitoring, logging, and security scanning.
• Good understanding of networking, IAM, containers, and cloud infrastructure security.

Good to Have

• Exposure to GPU/cloud infrastructure and AI model deployment.
• Experience with tools such as Prometheus, Grafana, OpenTelemetry, ELK, or similar.
• Knowledge of DevSecOps and tools such as Trivy, Snyk, SonarQube, Checkov, or equivalent.
• Experience with Helm, ArgoCD, or GitOps.
• Familiarity with cloud-native security and cost optimization.

What We're Looking For

A hands-on DevOps professional who can automate infrastructure, improve deployment reliability, secure cloud environments, and support modern AI workloads in a fast-paced remote engineering environment.