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Clinical Development Lead, AI​/LLM Medical Excellence Hybrid Clinical Development Lead, AI​/LLM

Job in New York, New York County, New York, 10261, USA
Listing for: Neko Health AB
Full Time, Part Time position
Listed on 2026-09-27
Job specializations:
  • Doctor/Physician
Salary/Wage Range or Industry Benchmark: 180000 - 280000 USD Yearly USD 180000.00 280000.00 YEAR
Job Description & How to Apply Below
Position: Clinical Development Lead, AI/LLM Medical Excellence • New York • Full time • Hybrid Clinical Development Lead, AI/LLM
Location: New York

Neko is redefining what prevention means, from treating illness when it arrives, to sustaining health before it's ever  mission: make data-driven, preventative care accessible to more people, before symptoms appear.
In a single, non-invasive visit under an hour, proprietary technology and direct clinical care combine to deliver personalised, actionable insights. It's a team that thinks in 10x, not 10%. Every role here plays a part in building a world where prevention is the norm, and where your work genuinely helps people live longer, healthier lives.

Role Purpose

We're looking for an exceptional Clinical Development Lead to own the clinical accuracy and safety of every generative AI surface Neko Health builds: the member-facing LLM chat, the Gen AI UX, Doctor Scribe, and Pre-brief. This is a high-impact role for a clinician who knows how to set the quality bar for generative output in a clinical context and then hold it.

You'll lead the LLM and AI pillar within Clinical product and development, partnering directly with the LLM and AI Product Manager and Engineering lead: one clinical lead to one pillar, alongside them rather than shared across them. Their goal is engagement, with members returning, using the chat, and trusting it to help them understand and navigate their health. You own the thing that makes engagement safe to want: clinical quality.

A generative surface someone uses ten times a year is only good if it is right every time. You set that bar, and you are the DRI for clinical safety of what these surfaces say.

We're post-Series B and moving quickly, and this area of work is about clinical judgement, evaluation rigour, and strong advisory capabilities.

What You’ll Deliver in the First 6-12 Months

Set clinical requirements and the quality bar for all generative AI surfaces, acting as clinical DRI from scoping through rollout.

Build and run the clinical evaluation framework for generative outputs, and define the acceptance threshold behind the >90% eval score.

Own the clinical safety case for member-facing chat: hallucination, unsafe or incorrect advice, and missed escalation.

Validate Doctor Scribe output against the auto-generated debrief and referral-accuracy targets.

Partner with the LLM and Gen AI PM and Engineering lead on the pillar roadmap, validating every release against clinical safety, accuracy and compliance.

Work alongside the Member Experience and Medical Tools clinical leads, plus Quality & Compliance, Learning & Education, Operations and market/clinic leadership, across the product lifecycle.

Carry a small, protected clinical commitment (roughly 0.05-0.1 FTE) to stay grounded in clinic reality.

A practising or recently practising physician with the credibility to set the clinical bar and act as DRI, or an equivalent clinical-scientific background with deep clinical fluency.

Direct experience with LLMs or generative AI in a healthcare or clinical-content setting: building, evaluating, or clinically validating generative outputs.

Strong grasp of the failure modes of generative models in a clinical context (hallucination, unsafe advice, missed escalation) and how to evaluate against them.

Working understanding of medical-device and clinical-software quality and safety obligations (e.g. EU MDR, GCP) as they apply to AI.

Ability to produce and validate specialist clinical content, not only to coordinate others who do.

Comfort operating across Swedish, UK and US clinical contexts, and the judgement to know when to override the tool with clinical reasoning.

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