Europe Arbeitnow ·
full-timeAI Enablement Engineer
Skin Analytics · London office based
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
| Role | AI Enablement Engineer |
|---|---|
| Company | Skin Analytics |
| Location | London office based |
| Type | full-time |
| Compensation | Not disclosed |
| Deadline | Rolling |
Typical process for this type of role
A general guide — the exact steps for this specific listing may vary; check the original posting for details.
- 1ApplicationSubmit your resume through the apply link.
- 2ScreeningRecruiter reviews your background against the role.
- 3AssessmentA technical test, assignment, or coding round, depending on the role.
- 4Interview(s)One or more rounds with the hiring team.
- 5OfferOffer letter with compensation and start date.
Before you apply
0/4More at Skin Analytics
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