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:
Digital Solution Engineering ManagerWhat 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 responsibilitiesIn this role, we are looking for an experienced Technical Lead – Enterprise AI Platforms & Applications to join our Industrial Automation Digital Organization. The role requires a strong technical leader with expertise in enterprise software engineering, AI platform development, cloud-native architectures, and Agile delivery practices. The candidate will be responsible for leading engineering teams in the development of scalable AI-enabled applications, Copilot solutions, Agentic AI workflows, and cloud-native services while ensuring engineering excellence, operational reliability, and delivery predictability.
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 Product Managers, Solution Architects, AI/ML Engineers, DevOps teams, Quality Engineering teams, Platform Engineering teams, and cross-functional business stakeholders.
You will be mainly accountable for:Product Development & Technical Leadership
• Provide technical leadership, establish coding standards, and drive engineering best practices for enterprise AI platform development.
• Design and develop High-Level Designs (HLD) and Low-Level Designs (LLD) for scalable AI services and applications involving Copilot systems, Agentic AI workflows, Model Context Protocol (MCP) integrations, LLMOps services, Python/.NET backend systems, and Angular-based applications.
• Create Work Breakdown Structure (WBS) plans to support feature implementation, sprint execution, release planning, and engineering deliverables.
• Ensure cybersecurity standards, secure coding practices, AI governance principles, prompt safety controls, and tenant isolation mechanisms are consistently implemented across engineering teams.
• Drive adoption of engineering best practices related to coding standards, testing methodologies, debugging approaches, observability frameworks, and operational excellence.
• Conduct code reviews, architecture reviews, and technical assessments to maintain engineering quality and adherence to established standards.
• Implement and enforce automated testing frameworks, CI/CD pipelines, deployment automation practices, and release management processes.
• Identify, troubleshoot, and resolve performance bottlenecks involving AI inference services, APIs, orchestration layers, and distributed application workloads.
• Develop and maintain technical documentation including architecture diagrams, deployment topologies, API specifications, solution designs, and engineering guidelines.
• Collaborate closely with Product Managers and Architects to define roadmaps, support MVP realization, and prioritize engineering initiatives.
• Ensure engineering documentation remains current, standardized, and readily accessible across development teams.
• Support scalable deployment patterns leveraging Kubernetes, asynchronous processing, caching strategies, and cloud-native architectural principles.
People Leadership & Team Management
• Mentor, coach, and provide technical guidance to engineering teams while supporting career development initiatives.
• Delegate responsibilities, manage sprint priorities, and ensure effective engineering execution aligned with quality and delivery objectives.
• Communicate effectively with cross-functional teams, Product Management, Architecture teams, and key stakeholders regarding technical progress and delivery status.
• Provide regular sprint updates, engineering status reports, and delivery metrics to leadership and stakeholders.
• Foster a collaborative, inclusive, and innovation-driven engineering culture focused on continuous improvement and technical excellence.
• Identify dependencies proactively and remove technical blockers to ensure smooth sprint execution and successful delivery outcomes.
• Collaborate effectively with DevOps, Cloud Engineering, Security, AI/ML, and Product Engineering teams to drive cross-functional execution.
Agile Delivery & Scrum Processes
• Act as a Scrum Technical Lead or work closely with Scrum Masters to ensure adherence to Agile methodologies and engineering practices.
• Facilitate and actively participate in sprint planning sessions, daily stand-ups, sprint reviews, retrospectives, backlog grooming, and engineering planning discussions.
• Encourage continuous improvement across engineering processes, automation capabilities, and delivery efficiency initiatives.
• Identify opportunities to optimize sprint execution, deployment processes, release activities, and operational workflows.
• Provide mentorship and coaching to team members on Agile engineering execution, delivery excellence, and software development best practices.
Qualifications for the role:• Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, Data Science, or a related technical discipline.
• 7+ years of experience in software engineering with demonstrated experience in technical leadership roles.
• Strong understanding of LLMOps principles, AI orchestration systems, Natural Language Processing (NLP) frameworks, and enterprise AI platform engineering.
• Experience with model monitoring, AI inference services, orchestration frameworks, and production-scale enterprise AI deployments.
• Hands-on expertise with Microsoft Azure cloud services including Azure OpenAI Service, Azure Kubernetes Service (AKS), Azure Cosmos DB, Azure App Services, Azure SQL Database, and cloud-native deployment models.
• Strong understanding of data structures, algorithms, asynchronous programming techniques, and scalable microservices architectures.
• Proven experience developing scalable backend systems, RESTful APIs, distributed services, and cloud-native AI-enabled platforms.
• Expertise in CI/CD pipelines, deployment automation, Kubernetes, Docker, observability practices, and engineering automation frameworks.
• Demonstrated ability to build secure, scalable, resilient, and highly available web applications and REST API services.
• Understanding of Industrial Internet of Things (IIoT) protocols and standards such as MQTT and OPC UA is preferred.
• Experience mentoring software engineers, conducting technical reviews, and promoting engineering excellence across teams.
• Strong analytical thinking, troubleshooting abilities, stakeholder management, communication, and technical documentation skills.
• Experience working within Agile/Scrum environments and leading engineering teams through iterative delivery models.
More about usABB is a leading global technology company that energizes the transformation of society and industry to achieve a more productive, sustainable future. The Process Automation (PA) business area automates, electrifies, and digitalizes some of the world's most complex industrial infrastructures.
Through its five divisions, ABB serves customers across energy, process, and hybrid industries – from hydrocarbons, chemicals, water, mining, minerals, pulp & paper to marine and ports, and many more. Process Automation stands at the heart of some of the most important shifts in society, helping energy-intensive industries operate more safely, intelligently, and sustainably to enable a prosperous, low-carbon future.
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.
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Skills Required
- Bachelor's or Master's degree in Computer Science, Engineering, AI, Data Science, or related discipline
- 7+ years of software engineering experience with demonstrated technical leadership
- Hands-on expertise with Microsoft Azure services including Azure OpenAI Service, AKS, Azure Cosmos DB, Azure App Services, Azure SQL Database
- Proven experience developing scalable backend systems, RESTful APIs, distributed services, and cloud-native AI-enabled platforms
- Strong understanding of LLMOps principles, AI orchestration systems, NLP frameworks, and enterprise AI platform engineering
- Expertise in Kubernetes, Docker, CI/CD pipelines, deployment automation, and observability practices
- Proficiency in Python and .NET backend development; experience with Angular frontends
- Experience with model monitoring, AI inference services, and production-scale enterprise AI deployments
- Strong knowledge of data structures, algorithms, asynchronous programming, and microservices architectures
- Experience mentoring engineers, conducting code and architecture reviews, and promoting engineering excellence
- Familiarity with secure coding practices, AI governance, prompt safety controls, and tenant isolation
- Understanding of IIoT protocols and standards such as MQTT and OPC UA
- Experience working in Agile/Scrum environments and acting as a technical lead for sprint delivery
ABB Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about ABB and has not been reviewed or approved by ABB.
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Healthcare Strength — Healthcare coverage is described as comprehensive, with medical, dental, vision, mental health support, and disability and life insurance included. Immediate eligibility in some roles reinforces the sense of dependable core coverage.
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Leave & Time Off Breadth — Time-off offerings are described as broad, including paid holidays, sick days, volunteer time, sabbaticals, and, in some cases, 25 days of PTO. Flexible scheduling and remote-work options add to perceived time-off and flexibility value.
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Retirement Support — Retirement benefits are positioned as robust, including a 401(k) with company contributions or matching and, in some cases, profit sharing or pension savings. Stock purchase/share acquisition programs complement longer-term savings options.
ABB Insights
What We Do
ABB is a leading global technology company that energizes the transformation of society and industry to achieve a more productive, sustainable future. By connecting software to its electrification, robotics, automation and motion portfolio, ABB pushes the boundaries of technology to drive performance to new levels. With a history of excellence stretching back more than 130 years, ABB’s success is driven by about 110,000 talented employees in over 100 countries. www.abb.com








