AI Enablement Engineer
Confirmed on the employer's own hiring board on Oct 21, 2026. First seen by Alion on Aug 13, 2026.
Want to join a team of passionate people who want to build a future where no one dies from skin cancer?
About us
Skin Analytics is an award-winning, health tech company that deploys world-leading skin cancer pathways using AI as a medical device, DERM.
Following our recent £15M series B funding, regulatory milestones hit, and doubling from 50 to 100 headcount in 2025, we're ready to scale further internationally, making history for AI in healthcare and the future of dermatology.
We're proud to epitomise AI for good - with a Class III CE mark, DERM is the only AI as a medical device approved to make clinical decisions autonomously in the cancer space, as well as being the first company to receive a NICE recommendation for use across the NHS.*
DERM is deployed at more than 28 NHS organisations where we enable patients to gain significantly quicker access to skin cancer diagnosis. If that's not enough, we also collaborate with some of the largest health insurers to reach patients in their own homes.
We are a team of passionate people on a mission to build a future where no one dies from skin cancer.
We are looking for an exceptional Senior AI Enablement Engineer to help transform the way Skin Analytics builds software.
This is a senior role, reporting into our VP of Technology, focused on enabling engineers, teams and the wider business to maximise the value of AI-assisted and agentic software development.
You will work alongside Engineering Managers, Senior Engineers, Product teams and business stakeholders to identify opportunities for AI-driven automation and productivity improvements across the entire software development lifecycle.
You will help define the future engineering operating model at Skin Analytics, introducing new tools, workflows, agents and ways of working that allow our teams to deliver more value with greater quality and speed.
This is a highly hands-on role. We are looking for someone who actively uses modern AI engineering tools every day and has practical experience delivering real software using agentic workflows.
Responsibilities
AI Engineering Enablement
Lead the 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, documentation, deployment and support.
Act as the subject matter expert for AI-assisted software engineering.
Create standards, patterns and best practices for the use of AI within Engineering.
Technical Leadership
Partner with Engineering Managers and Senior Engineers to improve team productivity and effectiveness, whilst maintaining quality and regulatory compliance.
Coach, mentor and train engineers in the practical use of AI tooling.
Establish metrics to measure the impact of AI tooling and automation initiatives.
Agentic Systems Development
Build and maintain internal AI agents and automation solutions, integrating capabilities into our platforms and workflows.
Evaluate and implement emerging AI tools and technologies.
Develop reusable prompts, workflows, agent architectures and engineering accelerators.
Work closely with Platform, DevOps and Security teams to ensure safe and scalable adoption.
Strategic Innovation
Help shape Skin Analytics’ AI strategy across Engineering and the wider business.
Evaluate emerging technologies and identify opportunities for competitive advantage.
Work with leadership to prioritise AI initiatives based on business impact.
Support the wider organisation in understanding how AI can improve operational efficiency.
Required experience
Leadership and Communication
Ability to influence technical and non-technical stakeholders.
Experience driving engineering transformation initiatives.
Strong coaching and mentoring skills.
Excellent communication and presentation abilities.
Comfortable working across multiple teams and disciplines.
AI and Agentic Engineering
Extensive hands-on experience with modern AI engineering tools such as Claude Code, Codex, Gemini, Cursor, Windsurf or equivalent.
Experience designing and implementing agentic workflows into software delivery processes.
Deep understanding of prompt engineering, context management and agent orchestration techniques.
Experience evaluating AI tooling and measuring productivity outcomes.
Understanding of AI governance, security and risk management considerations.
Software Engineering
Strong software engineering background with significant experience building production systems.
Experience with JavaScript, TypeScript, Node.js, Cloud platforms such as AWS and Git-based development workflows.
Understanding of software architecture and system design.
Experience working within CI/CD environments.
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
Yellownest Salary Sacrifice Nursery Scheme - save with workplace nursery scheme
Bike to work scheme
Training budget
Weekly catch-ups, monthly meetings to talk about you, your ambitions and work on your development
Lots of fun social activities!
Our Values
Building a Strong Foundation
Always Learning
Lead from the Front
Tough and Resilient
The Real Stuff
Skin Analytics embraces and is committed to diversity and equal opportunities. We are dedicated to building a team that represents a variety of backgrounds, perspectives, and skills. The more inclusive we are, the better our work will be. If you need any adjustments during our hiring process, you can indicate that at the next step.
AI usage in our hiring process
If you submit an application to us, you will consent to AI playing a role in your hiring process. No hiring decision is ever made by an algorithm alone. Every AI-generated summary, screening result, or note is reviewed, verified, and, if necessary, corrected by a member of our recruitment team. Humans make the final call on who moves forward and who receives an offer.
You can find more information about how we use AI in our hiring process here.