Principal, Automation Enablement Lead

At GSK, we unite science, technology and talent to get ahead of disease together. We are a global biopharma company with a special purpose – to unite science, technology and talent to get ahead of disease together. We’re proud to be leading a healthcare revolution, and we’re looking for people who can help us deliver on our ambition.

The Automation Enablement Lead makes it possible for DPTF (Digital Platforms and Technology Foundations) teams to build AI capability themselves. The role owns the golden pattern library and paved paths teams build against, drives adoption of AI-First delivery practice within DPTF's governed delivery lifecycle, runs the community of practice, and drives the AI skills uplift that turns platform engineers into people who can deliver AI without central support.

Platform teams own the outcomes. This role makes those outcomes achievable, and its success is measured by how much AI work happens outside the hub, not inside it. Solution delivery sits with the Director, Automation Engineering / Product Manager. Architectural standards and governance sit with the Director, Automation Platform Architect, and this role packages them into something teams can adopt. Delivery method for DPTF sits with the Senior Principal, Agile CoE, and the governed delivery lifecycle itself is owned through the GSK quality management system.

Key Responsibilities

• Own the golden pattern library and paved paths for AI delivery across DPTF, publishing the architectural standards set by the Director, Automation Platform Architect in a form platform teams can adopt, so that many teams build in one dialect instead of each inventing its own.

• Drive adoption of AI-First delivery practice across platform teams within DPTF's governed delivery lifecycle, so that eval gates, cost governance and provenance controls are inherited by any team using the paved paths.

• Drive AI skills uplift across platform engineering, building the capability that removes the need for dedicated AI headcount in every team.

• Run the AI community of practice and the associated governance forums, spreading what works between platform teams and surfacing what is not working.

• Publish and maintain the pattern library, reference implementations and guidance so that teams can adopt without asking.

• Work with talent and hiring leads so that AI fluency becomes an expectation of new platform engineering hires, not a specialism.

• Coach platform teams through their first AI deliveries, withdrawing support deliberately as their capability matures.

• Feed practical experience from platform teams back into the patterns, so standards reflect what works in delivery, not what looks right centrally.

• Translate Enterprise AI standards and Responsible AI policy into patterns and pipeline controls that platform teams can actually apply.

• Measure adoption of patterns, pipeline usage and AI capability across platform teams, and target enablement where uptake is weakest.

• Identify where a capability should become a shared primitive rather than a repeated pattern, and raise it with the Director, Automation Engineering / Product Manager.

• Hold the boundaries with the Director, Automation Engineering / Product Manager on solution delivery and shared primitives, the Director, Automation Platform Architect on architectural standards and governance, the Senior Principal, Agile CoE on DPTF delivery method, AI Ops on production readiness, and the platform teams on their own delivery.

Basic Qualifications

• Degree in Computer Science, Engineering, or a related discipline, or equivalent practical experience.
• Demonstrated experience in engineering, including hands-on software development, AI or, machine learning delivery experience.

• Experience setting patterns, standards or reference implementations adopted by teams outside direct control.

• Experience embedding automated quality and evaluation gates into a delivery toolchain that operates within a governed lifecycle.

• Experience building capability in other engineers through coaching, community practice or structured enablement.

• Experience translating enterprise standards and policy into something delivery teams can practically apply.

• Experience measuring adoption and acting on where uptake is weak.

• Experience working across multiple technology domains rather than within a single platform.

• Familiarity with Responsible AI requirements and how they are implemented in a delivery pipeline.

Preferred Qualifications

• Professional certifications desirable (e.g., cloud or machine learning platform certifications, coaching or technical enablement accreditation).
• Hands-on experience applying AI-first automation, including agents, workflows and integrations, to solve practical business and technical challenges.
• Good understanding of the pharma value chain, including R&D, manufacturing and commercial environments, and how technology and automation can support these areas.
• Experience documenting and redesigning processes and workflows, including the development of clear RACI models, SOPs and supporting documentation.
• Ability to build standards that teams adopt willingly.
• Strong coaching and facilitation skills across teams in different locations and domains.
• Excellent written communication, since patterns, process documentation and guidance are often consumed without the author present.

Work Arrangements:
This role offers a hybrid working model, with a mix of on-site and remote work. Fully remote or home-working arrangements are not available for this role.

Closing Date for Applications – 1 November 2026 EOD

Please take a copy of the Job Description, as this will not be available post closure of the advert.
When applying for this role, please use the ‘cover letter’ of the online application or your CV to describe how you meet the competencies for this role, as outlined in the job requirements above. The information that you have provided in your cover letter and CV will be used to assess your application.

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Skills

AI Agents, AI Enablement, AI Governance, AI Platforms, Architectural Patterns, Artificial Intelligence (AI), Data Integrity, Developer Engagement, Digital Fluency, Engineering Standards, Enterprise Architecture (EA), Generative AI, GxP Regulations, Lean Management, ML Platforms, Platform Engineering, Problem Solving, Software Engineering, Standards Compliance, Technical Coaching, Technical Enablement

Why GSK?

Uniting science, technology and talent to get ahead of disease together.

GSK is a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together. We aim to positively impact the health of 2.5 billion people by the end of the decade, as a successful, growing company where people can thrive. We get ahead of disease by preventing and treating it with innovation in specialty medicines and vaccines. We focus on four therapeutic areas: respiratory, immunology and inflammation; oncology; HIV; and infectious diseases – to impact health at scale.

People and patients around the world count on the medicines and vaccines we make, so we’re committed to creating an environment where our people can thrive and focus on what matters most. Our culture of being ambitious for patients, accountable for impact and doing the right thing is the foundation for how, together, we deliver for patients, shareholders and our people.

GSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), military service or any basis prohibited under federal, state or local law.

We believe in an agile working culture for all our roles. If flexibility is important to you, we encourage you to explore with our hiring team what the opportunities are.

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