Siemens Healthineers
Create a free account
One signup unlocks everything for this job:
- See your personalized profile match score
- See the skills this role is missing for you
- Apply to this job and track your application
- Generate an AI cover letter for this role
Bengaluru · On-site · 2-5 Yrs · 6 days 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
Job Requirements 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 recent 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. Cloud Infrastructure & Platform Operations
- 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. DevOps & Automation
- 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. AI & MLOps Support
- 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. Monitoring & Reliability
- Implement monitoring and alerting with Prometheus, Grafana, ELK Stack, or cloud-native tools.
- Resolve incidents, run root cause analyses, and optimize performance. Improve system reliability, scalability, and availability.
- 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. Cloud Infrastructure & Platform Operations
- Design, deploy, and maintain cloud infrastructure on Azure or AWS.
- Operate Kubernetes and container platforms for application and AI workloads.
Qualifications
- 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). Cloud Platforms
- Hands-on experience with at least one cloud platform: Microsoft Azure (preferred), AWS or GCP. Containers & Orchestration
- Docker
- Kubernetes (basic to intermediate)
- Helm, including building reusable charts for teams to use Infrastructure as Code
- Terraform and/or ARM Templates / Bicep, including building reusable modules
- Ansible (basic knowledge) Programming & Scripting
- Python, PowerShell, Bash, C#
- Experience automating workflows and building developer tools CI/CD & Version Control
- Azure DevOps and/or GitHub Actions
- Git-based workflows Monitoring & Logging
- Prometheus, Grafana, ELK Stack, Azure Monitor or similar tools Operating systems
- 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.
- Track record of identifying AI use cases that improve efficiency and scalability.
- Understanding of responsible AI, governance, and human-in-the-loop practices.
Verify Python for this role
Free PRACTICE for Python adds a verified skill signal that can boost how roles like this rank for you — optional, not required to browse or apply.
Sign up — verify Python free →Want match scores and deeper insight? Create a free candidate profile
Job application FAQ
Last updated 31 October 2026
- How do I apply for DevOps Engineer – Agentic Engineering (Bengaluru) 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 (Bengaluru) 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 (Bengaluru) 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 (Bengaluru) role at Siemens Healthineers?
- This is a mid-level DevOps Engineer – Agentic Engineering (Bengaluru) role. Key skills include skills listed in the job description. Feedback AI highlights matched vs missing skills on your profile after signup.