{"id":3261846,"url":"https://alion.io/job/siemens-healthineers-devops-engineer-agentic-engineering","title":"DevOps Engineer – Agentic Engineering","company":{"id":20165,"name":"Siemens Healthineers","domain":"siemens-healthineers.com","url":"https://alion.io/company/siemens-healthineers","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Phenom","truth_index":{"grade":"A","score":100,"open_postings":4,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":25,"computed_at":"2026-10-30T05:48:23Z"}},"role":"DevOps","role_family":"DevOps","seniority":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AIOps","optional":false},{"name":"Ansible","optional":false},{"name":"AutoGen","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Azure DevOps","optional":false},{"name":"Bash","optional":false},{"name":"Bicep","optional":false},{"name":"C#","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Grafana","optional":false},{"name":"Helm","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Kubeflow","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"MLFlow","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Platform Engineering","optional":false},{"name":"PowerShell","optional":false},{"name":"Prometheus","optional":false},{"name":"Python","optional":false},{"name":"Semantic Kernel","optional":false},{"name":"Terraform","optional":false},{"name":"Windows","optional":false},{"name":"Agile","optional":true},{"name":"GitOps","optional":true},{"name":"LLM","optional":true}],"status":"live","first_seen_at":"2026-10-26T05:59:56Z","employer_posted_date":"2026-10-26","last_verified_at":"2026-10-30T18:38:39Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"Job RequirementsWe are seeking a passionate and motivated DevOps Engineer with exposure to AI and Cloud Technologies to join our growing team. This role is ideal for professionals with 1+ years of experience in DevOps, Cloud Infrastructure, Platform Engineering, or Site Reliability Engineering (SRE) who are looking to expand their expertise in AI infrastructure, automation, and cloud-native technologies.\nThe successful candidate will build agentic AI solutions on Azure that boost efficiency for our team and for the development teams using our cloud infrastructure and deployment tools. You'll embed AI agents into our cloud runtime and CI/CD pipelines, with governance and human-in-the-loop oversight, to automate routine tasks and speed up provisioning and deployments.\nKey Responsibilities\nAgentic Engineering\nIdentify AI use cases that boost efficiency and let us scale to more teams and partners without proportional effort.\nPinpoint manual work that grows with every new team or partner, such as onboarding, provisioning, and support requests.\nDesign and build AI agents for the selected use cases, from prototype to production.\nEmbed agents into CI/CD pipelines, provisioning workflows, and the cloud runtime.\nOperate, monitor, and maintain agents in production.\nEnforce governance, guardrails, and human-in-the-loop approval for agent actions.\nMeasure efficiency and scalability gains, and continuously improve agent quality, reliability, and cost.\nCloud Infrastructure & Platform Operations\nDesign, deploy, and maintain cloud infrastructure on Azure or AWS.\nOperate Kubernetes and container platforms for application and AI workloads.\nAutomate infrastructure provisioning with Infrastructure as Code (IaC).\nBuild and maintain Helm charts for application deployments.\nTroubleshoot infrastructure, networking, and deployment issues.\nDevOps & Automation\nBuild and maintain CI/CD pipelines with Azure DevOps, GitHub Actions, or similar tools.\nAutomate operational tasks with PowerShell and C#.\nDrive release management, deployment automation, and environment provisioning.\nUse AI-powered tools to increase operational efficiency.\nAI & MLOps Support\nDeploy and monitor AI/ML applications and services.\nMaintain MLOps workflows with Azure ML, MLflow, or Kubeflow.\nMonitor performance of AI workloads and their infrastructure.\nMonitoring & Reliability\nImplement monitoring and alerting with Prometheus, Grafana, ELK Stack, or cloud-native tools.\nResolve incidents, run root cause analyses, and optimize performance.\nImprove system reliability, scalability, and availability.\nRequired Technical Skills\nAgentic Engineering\nHands-on experience building AI agents with LLMs\nFamiliarity with agent frameworks such as Semantic Kernel, AutoGen, or LangChain\nExperience integrating agents with tools, APIs, and knowledge sources (e.g., MCP, RAG)\nUnderstanding of AI governance, guardrails, and human-in-the-loop patterns\nAbility to evaluate and monitor agents for quality, reliability, and cost\nAbility to identify use cases where AI improves efficiency and scalability\nExposure to Azure ML, Kubeflow, or MLflow.\nUnderstanding of AI-assisted operations (AIOps).\nCloud Platforms\nHands-on experience with at least one cloud platform: Microsoft Azure (preferred), AWS or GCP.\nContainers & Orchestration\nDocker\nKubernetes (basic to intermediate)\nHelm, including building reusable charts for teams to use\nInfrastructure as Code\nTerraform and/or ARM Templates / Bicep, including building reusable modules\nAnsible (basic knowledge)\nProgramming & Scripting\nPython, PowerShell, Bash, C#\nExperience automating workflows and building developer tools\nCI/CD & Version Control\nAzure DevOps and/or GitHub Actions\nGit-based workflows\nMonitoring & Logging\nPrometheus, Grafana, ELK Stack, Azure Monitor or similar tools\nOperating systems\nLinux\nWindows\nPreferred Qualifications\nBachelor's degree in Computer Science, IT, Engineering, or a related field.\n1+ years in DevOps, Cloud/Infrastructure Engineering, Platform Engineering, or SRE.\nHands-on experience with Docker and Kubernetes.\nSolid understanding of CI/CD and deployment automation.\nFamiliarity with Infrastructure as Code.\nBasic knowledge of AI/ML deployment and MLOps.\nExperience building and running AI agents or LLM-based solutions, ideally on Azure.\nTrack record of identifying AI use cases that improve efficiency and scalability.\nUnderstanding of responsible AI, governance, and human-in-the-loop practices.\nKnowledge of cloud security and networking basics.\nExperience working in Agile teams.\nAzure, Azure AI, AWS, Kubernetes, or Terraform certifications are a plus.\nNice-to-Have Skills\nKnowledge of GitOps practices.\nExperience with container security and vulnerability management.\nFamiliarity with distributed systems and microservices architectures.\nBenefits\nDevOps Engineer - Agentic Engineering\nLocation: Bengaluru, India\nExperience: 2-5 Years\nPosition Summary\nWe are seeking a passionate and motivated DevOps Engineer with exposure to AI and Cloud Technologies to join our growing team. This role is ideal for professionals with 1+ years of experience in DevOps, Cloud Infrastructure, Platform Engineering, or Site Reliability Engineering (SRE) who are looking to expand their expertise in AI infrastructure, automation, and cloud-native technologies.\nThe successful candidate will build agentic AI solutions on Azure that boost efficiency for our team and for the development teams using our cloud infrastructure and deployment tools. You'll embed AI agents into our cloud runtime and CI/CD pipelines, with governance and human-in-the-loop oversight, to automate routine tasks and speed up provisioning and deployments.\nKey Responsibilities\nAgentic Engineering\nIdentify AI use cases that boost efficiency and let us scale to more teams and partners without proportional effort.\nPinpoint manual work that grows with every new team or partner, such as onboarding, provisioning, and support requests.\nDesign and build AI agents for the selected use cases, from prototype to production.\nEmbed agents into CI/CD pipelines, provisioning workflows, and the cloud runtime.\nOperate, monitor, and maintain agents in production.\nEnforce governance, guardrails, and human-in-the-loop approval for agent actions.\nMeasure efficiency and scalability gains, and continuously improve agent quality, reliability, and cost.\nCloud Infrastructure & Platform Operations\nDesign, deploy, and maintain cloud infrastructure on Azure or AWS.\nOperate Kubernetes and container platforms for application and AI workloads.\nAutomate infrastructure provisioning with Infrastructure as Code (IaC).\nBuild and maintain Helm charts for application deployments.\nTroubleshoot infrastructure, networking, and deployment issues.\nDevOps & Automation\nBuild and maintain CI/CD pipelines with Azure DevOps, GitHub Actions, or similar tools.\nAutomate operational tasks with PowerShell and C#.\nDrive release management, deployment automation, and environment provisioning.\nUse AI-powered tools to increase operational efficiency.\nAI & MLOps Support\nDeploy and monitor AI/ML applications and services.\nMaintain MLOps workflows with Azure ML, MLflow, or Kubeflow.\nMonitor performance of AI workloads and their infrastructure.\nMonitoring & Reliability\nImplement monitoring and alerting with Prometheus, Grafana, ELK Stack, or cloud-native tools.\nResolve incidents, run root cause analyses, and optimize performance.\nImprove system reliability, scalability, and availability.\nRequired Technical Skills\nAgentic Engineering\nHands-on experience building AI agents with LLMs\nFamiliarity with agent frameworks such as Semantic Kernel, AutoGen, or LangChain\nExperience integrating agents with tools, APIs, and knowledge sources (e.g., MCP, RAG)\nUnderstanding of AI governance, guardrails, and human-in-the-loop patterns\nAbility to evaluate and monitor agents for quality, reliability, and cost\nAbility to identify use cases where AI improves efficiency and scalability\nExposure to Azure ML, Kubeflow, or MLflow.\nUnderstanding of AI-assisted operations (AIOps).\nCloud Platforms\nHands-on experience with at least one cloud platform: Microsoft Azure (preferred), AWS or GCP.\nContainers & Orchestration\nDocker\nKubernetes (basic to intermediate)\nHelm, including building reusable charts for teams to use\nInfrastructure as Code\nTerraform and/or ARM Templates / Bicep, including building reusable modules\nAnsible (basic knowledge)\nProgramming & Scripting\nPython, PowerShell, Bash, C#\nExperience automating workflows and building developer tools\nCI/CD & Version Control\nAzure DevOps and/or GitHub Actions\nGit-based workflows\nMonitoring & Logging\nPrometheus, Grafana, ELK Stack, Azure Monitor or similar tools\nOperating systems\nLinux\nWindows\nPreferred Qualifications\nBachelor's degree in Computer Science, IT, Engineering, or a related field.\n1+ years in DevOps, Cloud/Infrastructure Engineering, Platform Engineering, or SRE.\nHands-on experience with Docker and Kubernetes.\nSolid understanding of CI/CD and deployment automation.\nFamiliarity with Infrastructure as Code.\nBasic knowledge of AI/ML deployment and MLOps.\nExperience building and running AI agents or LLM-based solutions, ideally on Azure.\nTrack record of identifying AI use cases that improve efficiency and scalability.\nUnderstanding of responsible AI, governance, and human-in-the-loop practices.\nKnowledge of cloud security and networking basics.\nExperience working in Agile teams.\nAzure, Azure AI, AWS, Kubernetes, or Terraform certifications are a plus.\nNice-to-Have Skills\nKnowledge of GitOps practices.\nExperience with container security and vulnerability management.\nFamiliarity with distributed systems and microservices architectures.","description_format":"text","description_chars":9696,"description_truncated":false,"requirements":{"experience_years_min":2,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":true},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"India","iso":"IN","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Diagnostic Tests & IVD","Precision Medicine","Medical Imaging Systems"],"lifecycle":[{"event":"open","at":"2026-10-26T05:59:56Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring 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