Siemens Healthineers
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Bengaluru · On-site · 2-5 Yrs · 1 day ago
Biotechnology · 10000+ Employees · Erlangen, Germany
We drive innovation to help humans live healthier and longer. The products, services and solutions offered by Siemens Healthineers help physicians, medical staff and healthcare providers prevent illnesses from occurring and to correctly diagnose and determine the right treatments for people who do become ill, helping them to recover faster. Every hour, more than 240,000 patients are touched by technologies provided by Siemens Healthineers. We are at the center of clinical decision making: Almost three-quarters of all critical clinical decisions are influenced by our solutions. Built on a 120-year history of innovation, today we are a global player with a strong heritage in German engineering. Just one year after X-rays were discovered by Wilhelm Conrad Roentgen in 1895, we created the world's first medical X-ray device. Our archives still hold a letter from Roentgen dating back to 1896 praising the quality of tubes provided by Siemens.
Hiring: Engineering
What employees say
+ Good Work Life Balance and culture.
− Average pay compared to Experience level
More reviews on the company profile.
Interview experience · Graduate Apprentice Trainee
Appeared for a campus hiring; there were 3 rounds one technical, followed by a managerial, and at last a HR round. Mainly, the questions depended on the panel you got, but a few of the panels focused on DSA and actual co
Easy difficulty · Bengaluru · 213 reports
More interview insightsJob description
Overview
We are seeking a passionate and motivated DevOps Engineer with exposure to AI and Cloud Technologies to join our growing team.
Responsibilities
- Identify AI use cases that boost efficiency and let us scale to more teams and partners without proportional effort.
- Pinpoint manual work that grows with every new team or partner, such as onboarding, provisioning, and support requests.
- Design and build AI agents for the selected use cases, from prototype to production.
- Embed agents into CI/CD pipelines, provisioning workflows, and the cloud runtime.
- Operate, monitor, and maintain agents in production.
- Enforce governance, guardrails, and human-in-the-loop approval for agent actions.
- Measure efficiency and scalability gains, and continuously improve agent quality, reliability, and cost.
- Design, deploy, and maintain cloud infrastructure on Azure or AWS.
- Operate Kubernetes and container platforms for application and AI workloads.
- Automate infrastructure provisioning with Infrastructure as Code (IaC).
- Build and maintain Helm charts for application deployments.
- Troubleshoot infrastructure, networking, and deployment issues.
- Build and maintain CI/CD pipelines with Azure DevOps, GitHub Actions, or similar tools.
- Automate operational tasks with PowerShell and C#.
- Drive release management, deployment automation, and environment provisioning.
- Use AI-powered tools to increase operational efficiency.
- Deploy and monitor AI/ML applications and services.
- Maintain MLOps workflows with Azure ML, MLflow, or Kubeflow.
- Monitor performance of AI workloads and their infrastructure.
- Implement monitoring and alerting with Prometheus, Grafana, ELK Stack, or cloud-native tools.
- Resolve incidents, run root cause analyses, and optimize performance.
- Identify AI use cases that boost efficiency and let us scale to more teams and partners without proportional effort.
- Pinpoint manual work that grows with every new team or partner, such as onboarding, provisioning, and support requests.
- Design and build AI agents for the selected use cases, from prototype to production.
- Embed agents into CI/CD pipelines, provisioning workflows, and the cloud runtime.
- Operate, monitor, and maintain agents in production.
- Enforce governance, guardrails, and human-in-the-loop approval for agent actions.
- Measure efficiency and scalability gains, and continuously improve agent quality, reliability, and cost.
- Design, deploy, and maintain cloud infrastructure on Azure or AWS.
- Operate Kubernetes and container platforms for application and AI workloads.
Qualifications
- We 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.
- The 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.
- Hands-on experience building AI agents with LLMs
- Familiarity with agent frameworks such as Semantic Kernel, AutoGen, or LangChain
- Experience integrating agents with tools, APIs, and knowledge sources (e.g., MCP, RAG)
- Understanding of AI governance, guardrails, and human-in-the-loop patterns
- Ability to evaluate and monitor agents for quality, reliability, and cost
- Ability to identify use cases where AI improves efficiency and scalability
- Exposure to Azure ML, Kubeflow, or MLflow.
- Understanding of AI-assisted operations (AIOps).
- Hands-on experience with at least one cloud platform: Microsoft Azure (preferred), AWS or GCP.
- Docker
- Kubernetes (basic to intermediate)
- Helm, including building reusable charts for teams to use
- Terraform and/or ARM Templates / Bicep, including building reusable modules
- Ansible (basic knowledge)
- Python, PowerShell, Bash, C#
- Experience automating workflows and building developer tools
- Azure DevOps and/or GitHub Actions
- Git-based workflows
- Prometheus, Grafana, ELK Stack, Azure Monitor or similar tools
- Linux
- Windows
- Bachelor's degree in Computer Science, IT, Engineering, or a related field.
- 1+ years in DevOps, Cloud/Infrastructure Engineering, Platform Engineering, or SRE.
- Hands-on experience with Docker and Kubernetes.
- Solid understanding of CI/CD and deployment automation.
- Familiarity with Infrastructure as Code.
- Basic knowledge of AI/ML deployment and MLOps.
- Experience building and running AI agents or LLM-based solutions, ideally on Azure.
Nice to have
- Knowledge of GitOps practices.
- Experience with container security and vulnerability management.
- Familiarity with distributed systems and microservices architectures.
- Knowledge of GitOps practices.
- Experience with container security and vulnerability management.
- Familiarity with distributed systems and microservices architectures.
Benefits
- DevOps Engineer – Agentic Engineering
- Location: Bengaluru, India
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Job application FAQ
Last updated 27 October 2026
- How do I apply for DevOps Engineer – Agentic Engineering at Siemens Healthineers?
- Open this job on Feedback AI and sign up free (or sign in). You can apply from the job detail page; match scores and skill gaps appear when your profile is complete. Siemens Healthineers may attach structured assessments to interview rounds after you apply.
- Does Feedback AI show a match score for this DevOps Engineer – Agentic Engineering role?
- Yes after you add a resume or skills. Match score ranks this role against your profile — skills met, gaps, level, and location — so you prioritise applications where fit is strongest.
- Is DevOps Engineer – Agentic Engineering remote or on-site in Bengaluru, Karnataka?
- This listing is marked on_site with location Bengaluru, Karnataka. Confirm details on the job description before applying.
- What skills matter for this DevOps Engineer – Agentic Engineering role at Siemens Healthineers?
- This is a mid-level DevOps Engineer – Agentic Engineering role. Key skills include skills listed in the job description. Feedback AI highlights matched vs missing skills on your profile after signup.