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).