Senior or Module Lead DevOps Engineers

Impetus; Bengaluru; On-site; INR 2,400,000 - 4,000,000; Full time

Job summary

Impetus in Bengaluru seeks an experienced Cloud Platform & MLOps Engineer to design and operate scalable AWS-based data platforms for ML workloads. You will implement IaC with Terraform, automate deployments, and optimize SageMaker, EKS, Lambda, S3, Glue, Athena, and Redshift in production.

You will build and maintain CI/CD pipelines for ML and data deployments, manage platform releases with GitHub Actions, ArgoCD, or Harness, and ensure high availability, security, and incident readiness across

Qualifications

• Strong hands-on experience with AWS cloud services such as SageMaker, EKS, Lambda, S3, Glue, Athena, Redshift.
• Proficiency in Terraform-based infrastructure provisioning and automation.
• Experience with Kubernetes administration and production deployments.
• Proficiency in Python and Linux shell scripting for automation.
• Hands-on experience with CI/CD tooling (GitHub Actions, ArgoCD, Harness).

Responsibilities

• Design, deploy, and support scalable AWS-based MLOps and data platforms.
• 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.
• Implement monitoring, logging, alerting, and observability solutions.
• Apply AWS security best practices across infrastructure and applications; ensure compliance and governance.

Skills

AWS Cloud

Terraform

Kubernetes / Amazon EKS

Python

CI/CD pipelines

Linux & Shell Scripting

Monitoring & Alerting

Production Support & Incident Mgmt

Cloud Security & Compliance

Tools

Harness

GitHub Actions

ArgoCD

MWAA / Airflow

Job description

• 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.

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
• 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)