Principal AI Engineer

Job Summary

The Principal AI Engineer is responsible for the technical design, development and implementation of AI-enabled and automation solutions across GSK s MES Development Team. The role combines hands-on AI/software engineering with technical leadership to deliver reusable agents, automation components, integrations and engineering tools. Working closely with the MES Automation Manager, the role translates the Global MES AI and automation strategy into practical solutions and drives the technical adoption of AI within the development team. The job holder coordinates AI-related engineering activities, guides and coaches developers, promotes common AI engineering practices and remains hands-on in prototyping, scripting, integration and solution development. The role ensures that AI-enabled solutions are reliable, secure, reusable, measurable and appropriately governed, including evaluation, human oversight, monitoring and traceability. The MES Automation Manager retains accountability for AI/automation strategy, governance and value realization, while the Principal AI Engineer provides the technical leadership and engineering capability required to implement and scale AI within MES Development Team. Drives the delivery and operational support of AI solutions across their lifecycle, ensuring reliable, secure, and scalable capabilities that enhance MES developer productivity, operational efficiency, and data-driven decision-making while delivering measurable business value and user adoption.

Key Responsibilities

• Design, develop, test and implement AI-enabled solutions, agents and automation capabilities supporting the MES Development Team.
• Work with the MES Automation Manager to translate the MES AI and automation strategy into prototypes, (Minimum Viable Product) MVPs and scalable production solutions.
• Lead the technical implementation and adoption of AI within the development team, coordinating AI engineering activities and coaching developers in AI-enabled ways of working.
• Develop reusable AI agents, services, integrations, (Application Programming Interfaces) APIs, automation components and AI-ready knowledge solutions applicable across MES development.
• Apply prompt and context engineering, retrieval/RAG (Retrieval-Augmented Generation), agent orchestration and tool integration to build reliable and effective AI solutions.
• Define and execute evaluation, testing, acceptance criteria and monitoring for AI-generated outputs and agent behavior, and implement appropriate human oversight, traceability, logging, access controls and exception handling for AI-enabled solutions.
• Apply professional software engineering practices using technologies such as Python, C#/.NET, SQL, PowerShell, (Representational State Transfer) REST APIs, JSON (JavaScript Object Notation)/XML (eXtensible Markup Language), Git/GitHub, automated testing and code review.
• Collaborate with Architecture, Product, MES Engineering, Infrastructure and other GSK AI and technology teams to align solutions with enterprise platforms, standards and reusable AI capabilities.
• Integrate AI capabilities with approved MES, engineering, knowledge and enterprise data sources, ensuring secure and controlled access, and ensure AI solutions comply with applicable Responsible AI, cybersecurity, data privacy, data integrity, (Good Practice ) GxP, validation and engineering requirements.
• Drive reuse, standardization and continuous improvement of AI engineering practices, components and knowledge across the MES Development Team.
• Use AI coding assistants and agent workflows as the default way of building, testing and documenting, and validates every output before it is committed or released.
• Deliver and support AI solutions across the full lifecycle, including CI/CD, release management, monitoring, incident resolution, and operational support, ensuring >99.5% availability, SLA compliance, and solution reliability. Drive AI-enabled capabilities that improve MES developer productivity, operational efficiency, and data-driven decision-making, with success measured through adoption, user satisfaction, delivery efficiency, incident reduction, and realized business value.

Basic Qualifications

• Bachelor's or master's degree in engineering, Computer Science, Information Technology, Automation, Data, Life Sciences or a relevant technical discipline, or equivalent practical experience.
• Relevant technical, AI, cloud, integration, automation, data, validation, cyber security or engineering certifications.
• Minimum 5+ years of hands-on technical engineering experience, including AI/software engineering in complex enterprise or operational technology environments.
• Experience in providing technical leadership for AI solution design, implementation, deployment and adoption, while remaining hands-on in development and problem solving.
• Experience in coordinating cross-functional engineering activities across development, architecture, infrastructure, data, AI/platform teams, vendors and specialist partners.
• Experience in technical troubleshooting, root-cause analysis and solution improvement across AI, software, integration and data layers.
• Experience in assessing technical risks and ensuring security, data integrity, resilience, Responsible AI, compliance and supportability requirements are addressed.
• Experience in coaching developers and supporting adoption of AI-enabled engineering practices, reusable patterns, standards and shared knowledge.
• Experience in supporting technical assurance, validation, audits or regulated-system governance in GxP or comparable controlled environments.
• Experience in collaborating, communicating and organising work effectively across global teams, suppliers and business stakeholders, including influencing decisions and building alignment.

Preferred Qualifications

• Experience in communication, facilitation and stakeholder management, including clearly articulating product decisions, priorities and technology constraints.
• Experience in using data, user feedback, AI and automation opportunities to inform product improvements and business outcomes.
• Experience in working in a collaborative, organized and user-focused way, including proficiency in using AI-powered tools to support productivity, decision-making and delivery quality.

Skills

• AI-enabled solutions
• Python
• C#/.NET
• REST APIs
• JSON/XML
• Git/GitHub
• PowerShell
• automated testing
• CI/CD

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.