Sr or Module Lead DevOps Engineers

• 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
  • Amazon Redshift

Infrastructure as Code

• Terraform
• Infrastructure provisioning and automation
• Environment management and deployment automation
• 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
• Production support and incident handling

Programming Scripting

• Strong Python programming skills
• Linux administration
• Shell scripting
• 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
• Cloud Security Compliance

Good-to-Have Skills

• Amazon SageMaker
• PySpark
• ArgoCD
• GitHub Actions
• AWS Lambda, AWS Glue
• Amazon Athena, Amazon Redshift
• 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)