This Position reports to: Digital Solution Engineering Manager

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 ABBs 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 contemporary 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

Bachelors or Masters degree in Computer Science, Engineering, Information Technology, Data Science, or a related discipline

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Senior Software Engineer (Bengaluru)
🏢 ABB India
📍 Bengaluru