Senior Software Engineer

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:

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 a Senior Software Engineer - AI Platforms & Applications to join our Industrial Automation Digital Organization. The role requires a highly motivated software engineer with strong expertise in developing enterprise-grade AI-enabled applications, scalable cloud-native services, and intelligent automation platforms. The candidate will be responsible for delivering high-quality software solutions across backend services, frontend applications, MLOps workflows, AutoML pipelines, and AI/ML platform integrations that support ABB's next-generation Industrial AI and Copilot platforms.

The work model for the role is: Hybrid

This role is contributing to the Digital Industry Analytics / Research & Development function in India. Main stakeholders include Architects, Technical Leads, AI/ML Engineers, DevOps teams, Product Management teams, Quality Engineering teams, and Platform Engineering teams.

You will be mainly accountable for:

Product Engineering & Development

. Design, develop, test, and maintain scalable enterprise applications using Python, Angular, REST APIs, and cloud-native technologies.

. Develop backend microservices, orchestration modules, and frontend components supporting AI-enabled applications and Copilot solutions.

. Build reusable APIs, asynchronous workflows, distributed processing services, and automation utilities to improve engineering efficiency and platform capabilities.

. Contribute to the development of features involving conversational AI, Retrieval-Augmented Generation (RAG) pipelines, document intelligence, AI workflows, and enterprise integrations.

. Participate actively in technical design discussions and contribute to High-Level Design (HLD) and Low-Level Design (LLD) activities for assigned components.

. Ensure software quality through adherence to coding standards, unit testing, integration testing, debugging, peer reviews, and continuous improvement practices.

. Optimize applications for scalability, performance, resiliency, and operational stability across cloud-native deployments.

. Develop and maintain technical documentation including API specifications, deployment procedures, design documents, and support guides.

MLOps & AutoML Engineering

. Develop and support MLOps workflows encompassing model training, deployment, monitoring, retraining, and lifecycle management activities.

. Build automation pipelines for model experimentation, feature engineering, hyperparameter tuning, and deployment orchestration.

. Integrate AI/ML models and inference services into enterprise applications and cloud-native platforms to deliver intelligent capabilities.

. Support observability, monitoring, telemetry, logging, and operational governance requirements for AI services and machine learning workloads.

. Collaborate with AI/ML Engineers and Data Scientists to productionize machine learning models and optimize inference performance.

. Utilize Azure Machine Learning, Kubernetes, Docker, and CI/CD pipelines to support scalable and reliable AI deployments.

Frontend & User Experience Engineering

. Develop responsive and scalable frontend applications using Angular, TypeScript, HTML, CSS, and modern user interface engineering practices.

. Implement reusable UI components, dashboards, visualization capabilities, and seamless API integrations.

. Ensure frontend solutions meet requirements for usability, accessibility, responsiveness, and performance optimization.

. Collaborate closely with UX/UI designers and backend engineering teams to deliver high-quality end-to-end user experiences.

Cloud, DevOps & Platform Engineering

. Support deployment, operations, and maintenance of applications hosted on Microsoft Azure cloud platforms and Kubernetes environments.

. Work with CI/CD pipelines, source control workflows, release automation, and infrastructure deployment processes to ensure efficient software delivery.

. Contribute to observability, monitoring, logging, alerting, and troubleshooting activities supporting enterprise applications and services.

. Ensure adherence to cybersecurity standards, secure coding practices, and enterprise governance requirements throughout the software development lifecycle.

Agile Delivery & Team Collaboration

. Participate actively in Agile/Scrum ceremonies including sprint planning, backlog refinement, daily stand-ups, sprint reviews, and retrospectives.

. Collaborate effectively with Architects, Technical Leads, QA teams, Product Owners, DevOps teams, and other stakeholders to deliver features and support release execution.

. Provide support for troubleshooting activities, root cause analysis, production stabilization, and defect resolution initiatives.

. Contribute to reusable engineering frameworks, automation initiatives, and continuous improvements that enhance development efficiency and product quality.

. Support knowledge sharing, peer learning, and technical collaboration initiatives across the engineering organization.

Ownership & Professional Expectations

. Take ownership of assigned modules, deliverables, and engineering activities, ensuring accountability for quality, timelines, and successful delivery outcomes.

. Demonstrate strong analytical thinking, troubleshooting capabilities, and engineering discipline in addressing complex technical challenges.

. Continuously enhance technical knowledge and adapt to emerging technologies related to Artificial Intelligence, cloud-native engineering, MLOps, and enterprise platform development.

. Maintain effective communication and stakeholder collaboration throughout all phases of the engineering lifecycle.

Qualifications for the role

. 6-10 years of experience in software engineering with strong expertise in developing enterprise-grade applications and cloud-native solutions.

. Proven hands-on experience with Python development for backend services, APIs, automation frameworks, and microservices architectures.

. Strong frontend development expertise using Angular, TypeScript, HTML, CSS, and modern UI engineering practices.

. Experience developing and integrating RESTful APIs, asynchronous processing workflows, and distributed applications.

. Solid understanding of Artificial Intelligence and Machine Learning concepts, including experience integrating AI capabilities into enterprise applications.

. Hands-on experience with MLOps practices, including model lifecycle management, deployment automation, monitoring, and retraining workflows.

. Exposure to Azure Machine Learning, Kubernetes, Docker, and cloud-native deployment models supporting scalable AI solutions.

. Familiarity with AutoML techniques, feature engineering processes, hyperparameter optimization, and model experimentation workflows.

. Experience with CI/CD pipelines, DevOps practices, source control systems, and release management processes.

. Understanding of observability principles including monitoring, logging, telemetry, and alerting for distributed applications.

. Strong analytical, problem-solving, and debugging skills with the ability to resolve complex technical issues.

. Experience working within Agile development methodologies and cross-functional engineering teams.

. Excellent communication, collaboration, and stakeholder management skills.

. Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, Data Science, or a related discipline.

More about us

ABB's Industrial Automation business is a global leader in driving digital transformation for asset-intensive industries. Through advanced software platforms, analytics, and domain expertise, ABB helps customers improve operational efficiency, reliability, and sustainability. The Digital Industry Analytics organization plays a critical role in delivering scalable, secure, and intelligent platforms that power ABB's next generation of Industrial AI solutions, Copilot experiences, and digital innovations. ABB India is committed to diversity and inclusion and provides equal employment opportunities to all qualified applicants. Employment may be subject to applicable background checks and pre-employment screening as per company policy.

Building a cleaner, smarter future takes all kinds of minds: the curious, the courageous, and the creative. We welcome people from all backgrounds and experiences.

Ready to make an impact Apply today or visit www.abb.com to learn more about the impact of our solutions across the globe.

Recruitment Fraud Warning

ABB never asks for payment from job applicants. All genuine job offers follow a formal application and interview process.

View current job openings and apply at:

For more information, read our full fraud warning notice at: