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
Workplace 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/Lead AWS Platform/DevOps Engineer (Bengaluru)
🏢 Impetus Consultrainers
📍 Bengaluru