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Über diese DevOps Engineer - Azure Databricks & Azure Cloud Operations Stelle bei Unisys

Unisys · Vor Ort · Bangalore, KA, India

What success looks like in this role:

• Design and provision a secure Azure AI Foundry ML architecture for OCR-based billing data extraction, taking models from validation through production deployment to resolve revenue-impacting invoice processing delays.
• Build and operate an end-to-end AI pipeline — ingestion, model inference, and REST API integration — Azure Container Apps, API Gateway
• Containerized Python/FastAPI microservices with Docker, publish images to Azure Container Registry, and deploy to Azure Container Apps, enabling scalable HTTP-based model serving.
• Build CI/CD pipelines (Azure DevOps) automating deployment and version control for ML-enabled infrastructure and application services.
• Implement pipeline monitoring and observability (Azure Application Insights, centralized logging) to track model and service performance in production.

• Designing and managing environments that combine on-premises infrastructure
with cloud services.
• Integrating AI-driven automation to streamline tasks like resource provisioning and security enforcement, enhancing efficiency and adaptability.
• Researching new technologies related to the development of distributed
applications on the Cloud platform


#LI-LS1

You will be successful in this role if you have:

BE degree with 2+ years relevant experience

  • Experience in DevOps and Cloud Operations.
  • Strong knowledge of Microsoft Azure services.
  • Experience with Azure Databricks (ADB).
  • CI/CD tools such as Azure DevOps, Jenkins, or GitHub Actions.
  • Scripting experience in Python, PowerShell, or Shell scripting.
  • Knowledge of Infrastructure as Code (Terraform, ARM templates, etc.).
  • Experience with monitoring and incident management.

Preferred Skills:

  • Experience supporting data platforms and analytics environments.
  • Knowledge of containers (Docker/Kubernetes).
  • Understanding of cloud security and governance.
  • AI/ML technical writer from the perspective of a perpetual learn
  • Distilled intricate topics into digestible content, catering to both novice learners and seasoned professionals in the field
  • Demystify the intricacies of computer vision, machine learning frameworks, and advanced neural network architectures

Unisys is proud to be an equal opportunity employer that considers all qualified applicants without regard to age, blood type, caste, citizenship, color, disability, family medical history, family status, ethnicity, gender, gender expression, gender identity, genetic information, marital status, national origin, parental status, pregnancy, race, religion, sex, sexual orientation, transgender status, veteran status or any other category protected by law.

Local employment practices and rights may vary by jurisdiction and are subject to applicable local laws. This commitment includes our efforts to provide for all those who seek to express interest in employment the opportunity to participate without barriers.

 

If you are a US job seeker unable to review the job opportunities herein, or cannot otherwise complete your expression of interest, without additional assistance and would like to discuss a request for reasonable accommodation, please contact our Global Recruiting organization at [email protected]. US job seekers can find more information about Unisys’ EEO commitment here.

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Über Unisys

Unisys is a global technology solutions company that powers breakthroughs for the world’s leading organizations. Our solutions – cloud, AI, digital workplace, logistics and enterprise computing – help our clients challenge the status quo and unlock their full potential. To learn how we have been helping clients push what’s possible for more than 150 years, visit unisys.com and follow us on LinkedIn . https://www.unisys.com/unisys-legal/recruiting Notice for U.S. Applicants: Unisys is an Equal Opportunity Employer – Minorities/ Females/ Veterans/ Individuals with Disabilities/ Sexual Orientation/ Gender Identity

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