Senior DevOps Engineer AI- ML

Job Description : Senior DevOps Engineer – Application Deployment Position :  Senior DevOps Engineer Location :  [Remote] Employment Type :  Full-time Experience :  6–10 years About the Role We are seeking a highly skilled Senior DevOps Engineer  with deep expertise in Terraform , AWS & Azure cloud platforms , and GitHub CI / CD .

You will be responsible for building and managing scalable cloud infrastructure, enabling reliable application deployments, and automating delivery pipelines.

Exposure to MLOps practices  (model deployment, monitoring, ML pipelines) will be considered a strong plus, as we are expanding towards AI / ML workloads in production.

Key Responsibilities Architect, implement, and manage Infrastructure as Code Terraform  for AWS and Azure.

Lead containerized application deployments  on AWS ECS Fargate , EKS , and Azure Kubernetes Service (AKS) .

Design, implement, and optimize CI / CD pipelines using GitHub Actions  for cloud-native applications.

Automate infrastructure and application scaling, networking, and monitoring across AWS and Azure.

Manage container orchestration using Docker, Kubernetes, and Helm charts .

Ensure observability  with CloudWatch, Azure Monitor, Prometheus, Grafana, ELK, or equivalent.

Enforce cloud security best practices  (IAM, RBAC, policies, OIDC, Key Vault / Secrets Manager).

Troubleshoot and resolve production issues  to maintain high availability and performance.

Collaborate with developers, cloud architects, and ML engineers on deployment pipelines.

Mentor junior DevOps engineers and drive adoption of DevOps and automation best practices .

Required Skills & Experience 6+ years  of DevOps / Cloud Engineering experience.

Terraform (mandatory)  – strong expertise with reusable modules, workspaces, and state management.

Advanced knowledge of AWS ECS Fargate , EKS , and supporting services.

Hands-on with Azure cloud services  (AKS, ACR, App Services, networking, DevOps / GitHub integrations).

Proven experience with GitHub Actions CI / CD  (workflows, runners, pipelines).

Strong proficiency with Kubernetes (EKS / AKS) , Helm, and container lifecycle management.

Monitoring and logging using CloudWatch, Azure Monitor, Prometheus, Grafana, or ELK.

Strong scripting ability (Python, Bash, PowerShell).

Security : IAM, RBAC, secrets management, Key Vault.

Preferred Qualifications Experience with MLOps pipelines  (model training / deployment automation, MLflow, Kubeflow, SageMaker, Azure ML).

Familiarity with GitOps workflows  (ArgoCD, Flux) and service mesh  (Istio, Linkerd).

Certifications : AWS DevOps Engineer Professional , Azure DevOps Engineer Expert , Terraform Associate .

Multi-cloud deployment expertise (AWS + Azure).

Cost optimization and performance tuning in cloud environments.

Soft Skills Strong problem-solving and analytical mindset.

Effective communicator and collaborator across cross-functional teams.

Ability to mentor and lead DevOps practices.

Adaptable to fast-paced, agile environments.

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