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.

Roles &
- Responsibilities

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
- Setting 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)

📌 Senior or Module Lead DevOps Engineers (Bengaluru)
🏢 Impetus
📍 Bengaluru