Senior DevOps Engineer - Cloud & MLOps
First seen by Alion on Nov 14, 2026.
Key Responsibilities :
Cloud Platform & MLOps :
- Design, deploy, and support scalable AWS-based MLOps and data platforms.
- Manage and optimize AWS services including SageMaker, EKS, Lambda, S3, Glue, Athena, and Redshift.
- Support ML model deployment, lifecycle management, model monitoring, and operational governance.
- Collaborate with data scientists and engineering teams to operationalize ML workflows and automate model delivery pipelines.
Infrastructure & Automation :
- Implement and manage Infrastructure as Code (IaC) using Terraform.
- Automate environment provisioning, configuration management, deployments, and operational workflows.
- Continuously improve platform reliability, scalability, and operational efficiency through automation.
- Maintain and enhance cloud infrastructure to meet business and operational requirements.
DevOps & Platform Engineering :
- Design, implement, and maintain CI/CD pipelines for application, data, and ML deployments.
- Manage platform releases and deployment processes using GitHub, ArgoCD, Harness, or similar tools.
- Troubleshoot deployment issues and support production environments.
- Ensure high availability, resilience, and operational readiness of cloud platforms.
Monitoring, Observability & Support :
- Implement monitoring, logging, alerting, and observability solutions.
- Proactively identify, troubleshoot, and resolve infrastructure and application issues.
- Support incident management, root cause analysis, and production issue resolution.
- Establish operational dashboards, health checks, and alerting mechanisms.
Security & Compliance :
- Apply AWS security best practices across infrastructure and applications.
- Implement IAM, network security, encryption, secrets management, and compliance controls.
- Ensure platform governance, auditability, and adherence to enterprise security standards.
- Support vulnerability remediation and security reviews.
Required Skills & Experience :
Cloud & AWS :
- Strong hands-on experience with AWS cloud services.
- Experience with: Amazon EKS, Amazon SageMaker, AWS Lambda, Amazon S3, AWS IAM, Amazon MWAA (Managed Airflow), AWS Glue, Amazon Athena, and Amazon Redshift.
Infrastructure as Code :
- Terraform, infrastructure provisioning and automation, environment management and deployment automation, and experience with Harness or similar deployment platforms.
DevOps & Platform Engineering :
- CI/CD pipeline implementation and management, GitHub-based development workflows, Kubernetes administration and operations, application deployment and release management, monitoring and observability practices, and production support and incident handling.
Programming & Scripting :
- Strong Python programming skills, Linux administration, shell scripting, and basic to intermediate PySpark knowledge.
Must-Have Skills :
- AWS Cloud, Terraform, Kubernetes / Amazon EKS, Python, CI/CD pipelines, Linux & Shell Scripting, Monitoring & Alerting, Production Support & Incident Management, and Cloud Security & Compliance.
Good-to-Have Skills :
- Amazon SageMaker, PySpark, ArgoCD, GitHub Actions, AWS Lambda, AWS Glue, Amazon Athena, Amazon Redshift, and Infrastructure Observability Platforms.
Data Platform Operations :
- Own AWS platform end-to-end across DEV, UAT, PROD environments.
- Manage CI/CD pipelines (build, test, deploy) and release governance.
- Drive Infrastructure as Code adoption for consistent, reproducible environments.
- Operate identity & access management (MFA, least privilege, identity governance).
- Ensure observability & reliability (logging, monitoring, alerting, incident readiness).
Skills
DevOps, MLOps, AWS, Terraform, Python, Kubernetes, CI/CD, Linux, Shell Scripting, Production Support, PySpark