{"id":4312705,"url":"https://alion.io/job/impetus-senior-devops-engineer-cloud-mlops","title":"Senior DevOps Engineer - Cloud & MLOps","company":{"id":6753,"name":"Impetus","domain":"impetus.com","url":"https://alion.io/company/impetus","size_band":null,"is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"DevOps","role_family":"DevOps","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon EKS","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"ArgoCD","optional":false},{"name":"AWS","optional":false},{"name":"AWS Glue","optional":false},{"name":"AWS Lambda","optional":false},{"name":"CI/CD","optional":false},{"name":"Configuration Management","optional":false},{"name":"GitHub","optional":false},{"name":"IAM","optional":false},{"name":"Incident Management","optional":false},{"name":"Kubernetes","optional":false},{"name":"Linux","optional":false},{"name":"Platform Engineering","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Terraform","optional":false},{"name":"GitHub Actions","optional":true},{"name":"Least Privilege","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-11-14T10:52:54Z","employer_posted_date":null,"last_verified_at":"2026-11-14T10:52:54Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"Key Responsibilities :\n\nCloud Platform & MLOps :\n\n- Design, deploy, and support scalable AWS-based MLOps and data platforms.\n\n- Manage and optimize AWS services including SageMaker, EKS, Lambda, S3, Glue, Athena, and Redshift.\n\n- Support ML model deployment, lifecycle management, model monitoring, and operational governance.\n\n- Collaborate with data scientists and engineering teams to operationalize ML workflows and automate model delivery pipelines.\n\nInfrastructure & Automation :\n\n- Implement and manage Infrastructure as Code (IaC) using Terraform.\n\n- Automate environment provisioning, configuration management, deployments, and operational workflows.\n\n- Continuously improve platform reliability, scalability, and operational efficiency through automation.\n\n- Maintain and enhance cloud infrastructure to meet business and operational requirements.\n\nDevOps & Platform Engineering :\n\n- Design, implement, and maintain CI/CD pipelines for application, data, and ML deployments.\n\n- Manage platform releases and deployment processes using GitHub, ArgoCD, Harness, or similar tools.\n\n- Troubleshoot deployment issues and support production environments.\n\n- Ensure high availability, resilience, and operational readiness of cloud platforms.\n\nMonitoring, Observability & Support :\n\n- Implement monitoring, logging, alerting, and observability solutions.\n\n- Proactively identify, troubleshoot, and resolve infrastructure and application issues.\n\n- Support incident management, root cause analysis, and production issue resolution.\n\n- Establish operational dashboards, health checks, and alerting mechanisms.\n\nSecurity & Compliance :\n\n- Apply AWS security best practices across infrastructure and applications.\n\n- Implement IAM, network security, encryption, secrets management, and compliance controls.\n\n- Ensure platform governance, auditability, and adherence to enterprise security standards.\n\n- Support vulnerability remediation and security reviews.\n\nRequired Skills & Experience :\n\nCloud & AWS :\n\n- Strong hands-on experience with AWS cloud services.\n\n- Experience with: Amazon EKS, Amazon SageMaker, AWS Lambda, Amazon S3, AWS IAM, Amazon MWAA (Managed Airflow), AWS Glue, Amazon Athena, and Amazon Redshift.\n\nInfrastructure as Code :\n\n- Terraform, infrastructure provisioning and automation, environment management and deployment automation, and experience with Harness or similar deployment platforms.\n\nDevOps & Platform Engineering :\n\n- 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.\n\nProgramming & Scripting :\n\n- Strong Python programming skills, Linux administration, shell scripting, and basic to intermediate PySpark knowledge.\n\nMust-Have Skills :\n\n- AWS Cloud, Terraform, Kubernetes / Amazon EKS, Python, CI/CD pipelines, Linux & Shell Scripting, Monitoring & Alerting, Production Support & Incident Management, and Cloud Security & Compliance.\n\nGood-to-Have Skills :\n\n- Amazon SageMaker, PySpark, ArgoCD, GitHub Actions, AWS Lambda, AWS Glue, Amazon Athena, Amazon Redshift, and Infrastructure Observability Platforms.\n\nData Platform Operations :\n\n- Own AWS platform end-to-end across DEV, UAT, PROD environments.\n\n- Manage CI/CD pipelines (build, test, deploy) and release governance.\n\n- Drive Infrastructure as Code adoption for consistent, reproducible environments.\n\n- Operate identity & access management (MFA, least privilege, identity governance).\n\n- Ensure observability & reliability (logging, monitoring, alerting, incident readiness).\n\nSkills\nDevOps, MLOps, AWS, Terraform, Python, Kubernetes, CI/CD, Linux, Shell Scripting, Production Support, 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