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 :

- AI/Cloud (Mandatory).

- 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 Were 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.