Senior Azure DevSecOps Engineer

Unisys India Private Limited; Bengaluru; On-site; INR 2,500,000 - 4,200,000; Full time

Job summary

Unisys India Private Limited in Bengaluru seeks a Senior Azure DevSecOps Engineer to design and run secure, automated cloud-native environments for AI projects. You will build and optimize CI/CD pipelines, automate infrastructure, and ensure scalable, observable systems across GPU-accelerated workloads.

The role emphasizes collaboration with security teams, strong scripting, and hands-on deployment in Azure, with a focus on AI lifecycle management and governance.

Qualifications

• Minimum 5 years of experience or equivalent combination of education and experience.
• Experience with DevOps tools (Jenkins, Azure DevOps, Terraform, Docker, etc.)
• Strong scripting and automation skills (e.g., Python, PowerShell, Bash)
• Strong knowledge of GPU-based systems and CUDA kernels, with ML model deployment using DVC
• Hands-on cloud experience, especially Microsoft Azure
• Familiarity with environment provisioning, access management, and deployment best practices for AI projects
• Excellent documentation and communication skills
• Experience onboarding and supporting technical teams

Responsibilities

• Provide DevSecOps engineering support for AI projects, incorporating modern cloud-native and AI-driven architectures.
• Design, implement, and manage automated infrastructure provisioning and configuration management solutions in Azure.
• Develop, maintain, and optimize robust CI/CD pipelines to automate build, test, and deployment for AI/ML workloads.
• Automate test case development and regression testing, including automated test suites for AI-based solutions.
• Support deployment, scaling, monitoring, and lifecycle management of containerized applications.
• Manage and document deployment pipelines and release processes; evolve toward modern DevOps platforms like Azure DevOps, Jenkins.
• Collaborate with cross-functional teams to troubleshoot environment, networking, and access issues.
• Implement monitoring/observability and alerting to track performance and detect anomalies.
• Identify bottlenecks and optimize components to improve efficiency, scalability, and responsiveness.
• Develop automation scripts for environment management and workflow standardization
• Maintain technical documentation related to environments, deployment processes, and AI integration
• Facilitate onboarding by providing access, documentation, and guidance on tools and best practices
• Collaborate with security teams to integrate security practices into pipelines, including vulnerability scanning
• Apply AI techniques to enhance DevSecOps, including automated testing and pipeline optimization

Skills

DevSecOps

CI/CD

Automation

Documentation

Cloud security

Tools

Jenkins

Azure DevOps

Terraform

Docker

Python

PowerShell

Bash

CUDA

DVC

Job description

Senior Azure DevSecOps Engineer

What success looks like in this role:

• Provide DevSecOps engineering support for AI projects, incorporating modern cloud-native and AI-driven architectures.
• Design, implement, and manage automated infrastructure provisioning and configuration management solutions, primarily within cloud platforms (e.g., Azure), including environment setup, access provisioning, and resource orchestration.
• Develop, maintain, and optimize robust CI/CD pipelines to automate build, test, and deployment processes, supporting AI/ML workloads.
• Automate test case development and regression testing, including the creation, maintenance, and expansion of automated test suites to ensure quality across ongoing and future releases, with particular focus on AI-based solutions.
• Support the deployment, scaling, monitoring, and lifecycle management of containerized applications, ensuring reliability, performance, and efficient resource utilization.
• Manage and document deployment pipelines and release processes, including both manual and automated workflows, and contribute to the adoption and migration toward modern DevOps platforms (e.g., Azure DevOps, Jenkins).
• Collaborate with cross-functional teams to troubleshoot environment, networking, and access issues, including firewall configuration, port management, and secure connectivity within cloud environments.
• Implement and maintain monitoring and observability solutions to track system performance, analyze trends, and detect anomalies, including configuring alerting mechanisms for proactive issue resolution.
• Identify performance bottlenecks and optimize system components (e.g., databases, application services, networking infrastructure) to improve efficiency, scalability, and responsiveness.
• Support code lifecycle management and DevSecOps strategy development, including version control practices, branching strategies, and release governance for both application and infrastructure code.
• Develop and enhance automation scripts and processes for environment management, data handling, and deployment operations, including environment resets and workflow standardization.
• Maintain comprehensive technical documentation related to environments, deployment processes, automation, and AI integration to support operational continuity and onboarding.
• Facilitate onboarding of team members by providing access, documentation, and guidance on environment setup, tools, and best practices.
• Collaborate with security teams to integrate security practices into development and deployment pipelines, including vulnerability scanning, access control, and compliance with enterprise and industry standards.
• Apply artificial intelligence (AI) techniques and tooling to enhance DevSecOps practices, including improving automated testing, anomaly detection, operational insights, and pipeline optimization.

#LI-SN1

You will be successful in this role if you have:

• Minimum 5 years of experience OR equivalent combination of education and experience.
• Experience with DevOps tools (Jenkins, Azure DevOps,Terraform,Docker, etc.)
• Strong scripting and automation skills (e.g., Python, PowerShell, Bash)
• Strong knowledge of GPU-based systems and CUDA kernels, along with experience in deploying machine learning models with versioning using DVC.
• Hands‑on experience with cloud environments, especially Microsoft Azure
• Familiarity with environment provisioning, access management, and deployment best practices for AI projects
• Excellent documentation and communication skills
• Experience onboarding and supporting technical teams

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. US job seekers can find more information about Unisys’ EEO commitment here.

Experience Level Senior Level