Principal Software Engineer - Tech Lead - Gen AI

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 an experienced Technical Lead Industrial AI Platforms to join our Industrial Automation Digital Organization. The role requires a highly motivated technology leader with strong expertise in developing enterprise AI applications, cloud-native platforms, and intelligent automation solutions. The candidate will be responsible for providing technical leadership and driving engineering excellence across Copilot solutions, Agentic AI workflows, MCP integrations, and LLMOps-enabled platforms built using modern cloud and software engineering practices.

The work model for the role is: Hybrid

You will be mainly accountable for:

• Provide technical leadership, establish coding standards, and drive engineering best practices for enterprise AI platform development.
• Design and develop scalable AI services and applications, including High-Level Design (HLD) and Low-Level Design (LLD), involving Copilot systems, Agentic AI workflows, MCP integrations, LLMOps services, Python/.NET backend systems, and Angular applications.
• Create Work Breakdown Structure (WBS) plans for feature implementation, sprint execution, and engineering deliverables.
• Ensure cybersecurity practices, secure coding standards, AI platform governance, and tenant isolation requirements are implemented across solutions.
• Drive engineering teams to follow best practices in coding, testing, debugging, observability, reliability, and operational excellence.
• Conduct code reviews and technical reviews to maintain engineering quality and ensure adherence to enterprise standards.
• Implement and enforce automated testing strategies, CI/CD pipelines, deployment automation, and release management practices.
• Identify and resolve performance bottlenecks across AI services, APIs, orchestration layers, and distributed workloads.
• Create and maintain technical documentation, including architecture diagrams, deployment models, API contracts, design specifications, and operational guides.
• Collaborate with Product Managers and Architects to define roadmaps, support MVP demonstrations, and prioritize engineering deliverables.
• Ensure engineering documentation remains updated, standardized, and accessible to development teams and stakeholders.
• Support scalable deployment patterns involving Kubernetes, asynchronous processing, caching mechanisms, and enterprise cloud-native services.
• Manage and mentor engineering teams by providing technical guidance, coaching, and career development support.
• Delegate tasks effectively, manage sprint priorities, and ensure engineering productivity and quality delivery.
• Communicate effectively with cross-functional teams, product management, architecture teams, and key stakeholders.
• Provide sprint status updates, engineering reports, and delivery metrics to leadership teams.
• Foster a collaborative, inclusive, and innovation-driven engineering culture.
• Review dependencies and proactively remove technical blockers to ensure smooth sprint execution and delivery progress.
• Collaborate closely with DevOps, Cloud, Security, AI/ML, and Product Engineering teams to ensure effective cross-functional execution.
• Act as a Scrum Technical Lead or work closely with Scrum Masters to ensure adherence to Agile methodologies.
• Facilitate sprint planning, daily stand-ups, sprint reviews, retrospectives, and engineering planning discussions.
• Drive continuous improvement initiatives focused on engineering processes, automation, and delivery efficiency.
• Identify opportunities to optimize sprint execution, deployment processes, and operational workflows.
• Provide coaching and mentoring on Agile engineering execution and delivery best practices.

Qualifications for the role

• Bachelors or Masters degree in Computer Science, Engineering, Artificial Intelligence/Machine Learning, or a related technical field.
• Proven experience of 7+ years in so…