AI Enablement Engineer

Overview

In this senior role, you enable AI-driven software engineering across Skin Analytics to accelerate delivery quality and value. You’ll partner with engineering leaders and product teams to embed AI-assisted and agentic workflows throughout the SDLC, with a focus on governance, safety and scalable automation. You help shape the engineering operating model and set standards for AI use. This role offers hands-on leadership at scale, contributing to a mission to reduce skin cancer mortality. You’ll work in a fast-growing, mission-driven environment at the intersection of healthcare and AI.

Pay / Benefits

• Competitive salary
• Share options package – all our employees have ownership in the company
• Private healthcare
• Company pension incl. salary sacrifice options
• 25 days annual leave + 5 day company shutdown in August + bank holidays
• Enhanced parental leave – includes adoption & foster care

Responsibilities

• Lead adoption of AI-assisted engineering practices across the organisation
• Identify opportunities to automate software delivery processes using AI and agentic tooling
• Design and implement AI-enabled workflows covering requirements, design, implementation, testing, deployment and support
• Act as subject matter expert for AI-assisted software engineering; create standards and best practices
• Partner with Engineering Managers and Senior Engineers to improve productivity while ensuring quality and regulatory compliance
• Coach, mentor and train engineers in practical AI tooling; establish metrics to measure impact
• Build and maintain internal AI agents and automation solutions; integrate capabilities into platforms and workflows
• Evaluate and implement emerging AI tools and technologies; develop reusable prompts, workflows and agent architectures
• Collaborate with Platform, DevOps and Security teams to ensure safe and scalable adoption
• Shape Skin Analytics’ AI strategy and prioritise initiatives based on business impact
• Support the wider organisation in understanding how AI improves operational efficiency

Key requirements

• Leadership and communication: influence stakeholders and drive engineering transformation
• Coaching and mentoring skills; excellent communication and presentation abilities
• Experience with modern AI engineering tools and agentic workflows; prompt engineering and orchestration
• Security, governance and risk management awareness in AI contexts
• Strong software engineering background; production systems experience
• Experience with JavaScript, TypeScript, Node.js; AWS or other cloud platforms; Git-based workflows; CI/CD environments

• Influential communication
• Cross-team collaboration
• Mentorship and coaching
• Claude Code
• Codex
• Gemini

…