Stealth HealthTech
AI Engineer
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Contract AI Engineer: Paid MVP Sprint, with a path to full-time
Stealth HealthTech | London / Remote
I’m building an advisor in aesthetic healthtech. It’s an AI conversational product that helps people understand their face holistically, including how sleep, hydration, diet and stress show up, so they walk into a clinic consultation informed rather than sold to.
This advisor is the first of several projects in our portfolio. Alongside it, we’re developing clinical tools in medical imaging and surgical AR, built with practising surgeons. The right engineer will have the chance to explore, and help shape, these next projects too.
Why join
- Start with a paid 2–4 week sprint, with the opportunity to move into a full-time founding engineering role as the company grows
- Work alongside top-tier talent: leading plastic surgeons, clinicians and researchers
- Shape a product from day one, with real influence over how it’s built
- Gain rare experience at the intersection of AI, healthtech and aesthetic medicine
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What you’ll do in the first phase
- Develop a prototype, and then develop into a working MVP
- Build a structured conversational flow that moves someone from an inquiry to a clear, answerable question, grounded in a curated clinical knowledge base (RAG)
- Build guardrails and escalation: knowing when to refer to a clinician, and generating a handoff summary a clinician can actually use
- Set up evaluation for clinical accuracy, not just fluency
- Design privacy-first data foundations (UK GDPR) and safeguarding against reinforcing appearance anxiety
What you’ll bring
- Degree in Computer Science, Biomedical Engineering, Software Engineering or a related field, or equivalent practical experience
- 2+ years’ experience, or a recent graduate with a product you’ve actually shipped
- Built and shipped LLM apps: RAG, prompting and evaluation
- Full-stack: React/TypeScript, plus Supabase or similar
- Face landmarking or computer vision, digital health / MedTech, or experience designing for user wellbeing
- Computer vision on medical images: detection and segmentation (e.g. YOLO, nnU-Net), small-data training with transfer learning, and calibrated uncertainty
- Real-time computer vision on video under tight latency budgets
- AR/XR engineering: 3D reconstruction, registration, stereo vision or SLAM
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The engagement
- Sprint until Dec 2026, starting late October
- Strong performance in the sprint leads to a conversation about a full-time role
- Details shared under NDA
- Compensation on milestone basis
To apply, email me with:
- Your CV
- A link to something you’ve built (GitHub, live app or demo)
- A brief summary on how you’d build an AI advisor that educates without giving medical advice
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