DevOps Engineer – AI/Cloud
First seen by Alion on Aug 25, 2026.
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.
Skills
DevOps, Cloud, Cloud Services, Artificial Intelligence, Docker, Kubernetes, Cloud Architect - AI/ML, Cloud Infrastructure, IT Infrastructure Automation, Machine Learning, MLOps