Description
The Automation Enablement Lead makes it possible for DTPF platform 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.
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.
- Drive adoption of AI-First delivery practice across platform teams within DPTF's governed delivery lifecycle.
- 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.
- Publish and maintain the pattern library, reference implementations and guidance.
- Work with talent and hiring leads so that AI fluency becomes an expectation of new platform engineering hires.
- Coach platform teams through their first AI deliveries.
- Feed practical experience from platform teams back into the patterns.
- Translate Enterprise AI standards and Responsible AI policy into patterns and pipeline controls.
- Measure adoption of patterns, pipeline usage and AI capability across platform teams.
- Identify where a capability should become a shared primitive rather than a repeated pattern.
- Hold the boundaries with the Director, Automation Engineering / Product Manager on solution delivery and shared primitives.
Professional Qualifications
- Degree in Computer Science, Engineering, or a related discipline.
- Professional certifications desirable.
Area of Specialisation
- AI enablement and capability building.
- AI-First delivery practice within a governed lifecycle.
Related Experience Required
- Overall 15 years and 8-10 years in engineering.
- Experience setting patterns, standards or reference implementations adopted by teams outside direct control.
- Experience embedding automated quality and evaluation gates into a delivery toolchain.
- Experience building capability in other engineers through coaching.
- Experience translating enterprise standards and policy into something delivery teams can practically apply.
Desirable
- Hands-on experience building AI-first automation.
- Comfortable technical fluency in modern AI/ML.
- Working knowledge of at least one pharma value chain area.
- Background in process documentation or workflow redesign.
Skills/Background
- Deep practical AI engineering knowledge.
- Ability to build standards that teams adopt willingly.
- Strong coaching and facilitation skills.
- Excellent written communication.