AI Engineer
Paloma Health
| Company | Paloma Health |
| Category | Engineering |
| Location | Hybrid: London Bridge office |
| Remote | Hybrid |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 28 Jul 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
AI Engineer
Location: Our preference is hybrid working: two days in the London office (Wed/Thu) and three days remote. We consider alternatives if this is not possible for you.
Office location: 140 Borough High Street, London, SE1 1LB
Reporting to: Avishai Gurt, VP Technology
About Paloma
In 2024, our founders, Mark and Darshak, were shocked to find that children needing an NHS autism or ADHD assessment were waiting 4-10 years for these assessments. Delayed assessments result in children being more likely to develop mental health conditions and fall behind in education. Furthermore, the much-needed pre/post-assessment support (outside of ADHD medications) is typically not funded by the NHS.
These long waits have built up due to increased recognition and understanding of neurodevelopmental conditions and a lack of investment and innovation within the NHS to meet the growing demand.
Mark and Darshak, with their 25 years of combined NHS experience, including building services that have treated over 1,000,000 patients in obesity & ophthalmology, founded Paloma to change this. Our mission is to make NHS autism and ADHD assessments and care accessible within 4 weeks of a GP referral, and, in turn, help every child achieve their potential.
As of May 2026, we have successfully reduced waits to 3 months by;
Taking a product-first approach to redesign the care pathway to give families a more consumer-like experience of care
Our in-house product, engineering and AI team building our own autism and ADHD specific electronic health record and AI documentation tool to free clinicians from their significant documentation burden to re-focus on supporting families
Investing in expanding the clinician workforce and upskilling them in new ways of working.
We are proud that Paloma is:
Loved by families, with 4.9 out of 5 Trustpilot and Google ratings
Care Quality Commission (CQC) registered and quality-focused
Clinically-led, with a team of 130 people, including over 80 clinicians supporting families through their assessment journey. We are hiring 100+ more roles over the next 12 months.
A community of passionate, mission-driven and innovative team members who challenge the status quo and test and learn from new ideas and approaches.
Backed by leading healthcare investors Triple Point and Heal Capital
What’s next?
Whilst we have reduced wait times, it is estimated that up to 500,000 children are still waiting for an NHS autism or ADHD assessment. We won’t rest until this comes down.
We want to build new services to support families and children diagnosed with autism or ADHD who feel lost after their assessments when the NHS is no longer there for them.
The Opportunity
Do you want to build AI-driven applications that directly help families get faster access to NHS children’s autism and ADHD assessments? This role is for you!
We seek a talented and passionate AI Engineer with proven experience building and evaluating AI-driven applications to join our dynamic AI squad, which sits within our wider product & engineering and expert clinical teams (your subject matter experts are within Paloma; you don’t need to wait for external stakeholders!).
You will be one of the founding members of the AI team at Paloma. The title is hands-on, but the scope is not small: you will help shape our evaluation culture, our tooling choices, and how the AI team grows from here.
You will work on:
Cutting-edge agentic AI product development and evaluation in partnership with our expert clinicians, product managers, and software developers, always focusing on how we improve staff efficiency and the family and child experience.
Building and running the evaluation pipelines for our AI products: creating gold-standard datasets, testing every prompt and pipeline change against them, and using the results to decide what ships
Developing our i