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Senior DevOps Engineer AI- ML
Donyati —Remote
- Full-time
- Remote
- Azure
- DevOps
- AWS
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Senior DevOps Engineer AI- ML

Donyati -
Remote

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Job details

Full-time

Qualifications

CI/CD
Performance tuning
Cloud infrastructure
Azure
Kubernetes
Software deployment
DevOps
Git
Bash (Unix shell)
RBAC
AWS
Docker
Terraform
Continuous integration
GitHub
Agile
AI
Communication skills
Python
PowerShell
AWS Certified DevOps Engineer – Professional
Identity & access management

Full job description

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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