R&D Engineer - DevOps & QE

At ABB, we help industries run leaner and cleaner—and every person here makes that happen. You’ll be empowered to lead, supported to grow, and proud of the impact we create together. Join us and help run what runs the world.

This Position reports to:

R&D Team Lead

What we believe in

ABB’s Process Automation business area enables customers to operate some of the world’s largest and most complex industrial infrastructures, helping them outrun – leaner and cleaner.

We offer a broad range of automation, electrification and digital solutions for process, hybrid and maritime industries, including industry-specific integrated control and software as well as measurement and analytics solutions and services.

Your role and responsibilities

In this role, we are looking for an experienced DevOps and Quality Engineering Specialist to join our Industrial Automation Digital Organization. You will contribute to the development, deployment, validation, and maintenance of Edge, Cloud, and Enterprise applications across the software development lifecycle.

The role requires strong hands-on expertise in DevOps, cloud infrastructure, containerization, Kubernetes, CI/CD, test automation, and quality engineering. You will work closely with Product Managers, Architects, Developers, DevOps, and other cross-functional stakeholders to ensure reliable infrastructure, efficient software delivery, and high-quality releases.

The work model for the role is: Hybrid

This role is contributing to Process Automation Digital in Bangalore.

You will be mainly accountable for:

• Design, implement, and maintain CI/CD pipelines and automated build, test, deployment, rollback, and release processes while supporting application deployments across Development, QA, UAT, and Production environments.

• Design, deploy, administer, and maintain highly available infrastructure across Azure, Red Hat Enterprise Linux (RHEL), Docker, Kubernetes, virtual machines, storage, networking, and security environments, ensuring reliability, performance, capacity optimization, and production readiness.