Senior AI Engineer

Twin Health

At Twin Health, we empower people to improve and prevent chronic metabolic diseases, like type 2 diabetes and obesity, with a new standard of care. Twin Health is the only company applying AI Digital Twin technology exclusively toward metabolic health.

We start by building a dynamic model of each person’s metabolism — drawing on thousands of data points from CGMs, smartwatches, and meal logs — that maps their personal path to better health. Guided by a dedicated clinical care team, our members have lowered their A1C below the diabetes range, achieved lasting weight loss, and reduced or even eliminated medications, all while living healthier, happier lives.

Working here

Our team at Twin Health is passionate, talented, and united by a shared purpose: to improve the metabolic health and happiness of our members. We believe in empowering every Twin to make a meaningful impact for our members, our clients, and each other, while enjoying a supportive, collaborative work environment.

Twin has been recognized not only for our innovation but also for our culture, including: Innovator of the Year by the Employer Health Innovation Roundtable (EHIR), selected to CB Insights’ Digital Health 150, and named one of Newsweek’s Top Most Loved Workplace® .

With more than $100 million raised in recent funding, including a $53 million Series E round in 2025 led by Maj Invest, and a $50 million investment in 2023 led by Temasek, Twin is scaling rapidly across the U.S. and globally. Backed by leading venture firms like ICONIQ Growth, Sequoia, Sofina, Temasek, and Peak XV, we are building the most impactful digital health company in the world.

Join us as we reinvent the standard of care in metabolic health.

Opportunity

We are seeking a Senior AI Engineer to join our Core AI team of AI Engineers and Data Scientists to take our AI-driven product to the next level using the latest techniques in Gen AI, AI agents, and deep learning. This is powered by our Digital Twin AI, which combines Predictive and Generative AI to provide individualized insights and recommendations that improve the health of our members everyday.

If you’re a hands-on AI Engineer who is excited to ship AI features used by members to fundamentally improve their health everyday, this is an excellent opportunity for you. Previous experience in healthcare is preferred, but not required.

Responsibilities

Drive the end-to-end lifecycle of AI products, from ideation and prototyping to development, deployment, and optimization.

Own the engineering quality of the AI system — evaluation frameworks, testing, CI pipelines for model behavior, and shared tooling used by the team.

Set and enforce engineering standards through code review: testing practices, abstractions, observability, and production reliability.

Apply advanced AI/ML and software engineering techniques to develop conversational AI agents, deep learning, and personalized recommendations to create “N of 1” solutions that adapt to individual needs.

Build and improve ML models to drive behavior change to achieve sustained improvements in metabolic health for a diverse member base across diabetes, weight loss, etc.

Influence product roadmap by deeply understanding member behavior and preferences through continuous data analysis.

Collaborate cross-functionally with our clinical, medical research, business analytics, and engineering teams to design end-to-end AI-powered experiences for our members and clinical teams and achieve metrics-driven impact.

Additional duties as assigned.

Qualifications

5+ years of industry experience developing AI and Machine Learning systems in production. Experience building consumer facing features a plus.

Strong software engineering fundamentals: testing, CI/CD, system design, code review. This is not a research role. Experience building evaluation infrastructure for LLM-based systems (not just running evals, but building the framework). Comfortable extending shared infrastructure and reviewing code at a senior SWE level.

Experience creating applications leveraging LLMs, Generative AI, advanced Prompt Engineering, RAG, and iterative AI evals.