# Automation Enablement Lead

**Company**: GSK
**Location**: Bengaluru
**Experience**: senior
**Job type**: full-time
**Category**: Engineering
**Industry**: Healthcare

**Apply**: https://gsk.wd5.myworkdayjobs.com/en-US/GSKCareers/job/Bengaluru-Luxor-North-Tower/Principal---Automation----Prompt---Agent-Engineer--with-specialization-in-domains-eg-DWP--Cloud--etc-_449192?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_57752c44-d14

## 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

- Drive adoption of AI-First delivery practice across platform teams within DPTF's governed delivery lifecycle

- Drive AI skills uplift across platform engineering

- 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 to ensure AI fluency is 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

- Hold the boundaries with various stakeholders

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

- Experience embedding automated quality and evaluation gates

- Experience building capability in other engineers

- Experience translating enterprise standards and policy

- Experience measuring adoption and acting on where uptake is weak

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

### Required
- Agentic AI
- Architecture Reviews
- Asset Life Cycle Management
- Data Integrity
- Design Assurance
- Digital Fluency
- GxP Regulations
- GxPs
- Lean Management
- Manufacturing Technologies
- Pharmaceutical Manufacturing
- Problem Solving
- Risk Awareness
- Standards Compliance
- Technology Architecture

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