engineering
Posted Jun 22AI Fullstack Engineer, Health Intelligence
at oura
Hybrid
Responsibilities
- Design and build LLM‑backed product capabilities: Ship user-facing features that use LLMs and other AI models to deliver personalized insights, guidance, and proactive notifications.
- Implement safe tool-calling, retrieval, and orchestration so that AI components behave deterministically where they must and adaptively where they can.
- Own evaluation, quality, and safety for AI workflows: Lead the design and implementation of evaluation frameworks and tooling to measure quality, safety, latency, and cost before and after release.
- Define the metrics and slices that matter for user-facing guidance, and integrate evals into the production pipeline.
- Integrate LLMs with personalization and understanding layers: Ground AI behavior in structured user context rather than one-off prompts.
- Collaborate with infrastructure and science teams on reasoning, planning, and multimodal use cases.
- Build robust, observable, and frontend-heavy systems: Design and implement services, workflows, and frontend components—built primarily in React—that meet strict reliability and performance expectations.
- A track record of working in product-facing teams, shipping to real users rather than only research prototypes, and caring about impact and iteration speed.
Requirements
- Our award-winning products help our global community gain a deeper knowledge of their readiness, activity, and sleep quality by using their Oura Ring and its connected app.
- The Health Intelligence team is at the forefront of integrating modern AI and LLMs into the Oura experience, transforming how members interact with and learn from their data.
- We are building the next generation of AI-powered health guidance at Oura, blending traditional ML with modern LLMs, reasoning systems, and robust evaluation - not as “chatbots with vibes,” but as rigorously evaluated components that explain decisions, surface trade-offs, and adapt member journeys over months and years.
- As an AI Engineer, you will design, build, and operate the systems that make this possible: LLM-backed workflows, retrieval and knowledge representations, evaluation pipelines, personalization logic, and the full stack product surfaces that together power Advisor, Adaptive Insights, notifications, and future navigation features. You’ll:
- Help turn ambiguous health questions into structured, testable AI systems.
- Connect AI components to navigation flows, product surfaces , and action systems so guidance turns into coherent, multi-step programs and one-tap actions, not isolated tips.
- Take ownership of operational health: debugging production issues, reducing technical debt, and iterating on architecture as the AI surface area and traffic grow.
- experience in AI engineering, with a multi-year frontend-heavy full stack product engineering, applied ML, or related roles building production systems.
- Strong proficiency building production systems across the stack, including user-facing product surfaces and backend services, and comfort working with cloud-native services to ship and maintain production features.
- Demonstrated ability to own systems end-to-end: from problem framing and data pipelines through modeling and prompting, all the way to deployment, monitoring, iteration, and product delivery.
- Comfort operating in a fast-changing AI/LLM domain with ambiguity, balancing rigor with pragmatism and keeping member value and safety at the center.
- Excellent communication and collaboration skills, including the ability to explain complex technical trade-offs to non-technical stakeholders and work effectively in cross-functional teams across time zones. Would be a benefit
- Experience with LLM evaluation and tooling: LLM-as-judge, rubric-based scoring, red-teaming, prompt versioning, or evaluation platforms (internal or external).
- Familiarity with RAG, knowledge graphs, or semantic retrieval systems (e.g., vector search, hybrid retrieval, ontologies, semantic layers) and how they integrate with LLMs.
- Background in personalization, recommendation, or ranking systems, including multi-objective optimization and guardrails for safety and fairness.
- Experience with developer tooling, experimentation frameworks, or analytics/observability products, especially internal tools used by multiple teams.
- Experience mentoring other engineers or scientists, or informally shaping best practices around AI/ML and evaluation in your team. •
- Experience with Python for backend services, data workflows, or AI integrations. What we offer Competitive salary Lunch benefit Wellness benefit
- If this sounds like the next step for you, please send us your application and CV as soon as possible. We aim to start interviewing as soon as suitable candidates are found.
Experience
- 2+ years of hands-on
Benefits
- An Oura ring of your own Wellness Time Off
- Individuals seeking employment at Oura are considered without regard to age, ancestry, color, gender (including pregnancy, childbirth, or related medical conditions), gender identity or expression, genetic information, marital status, medical condition, mental or physical disability, national origin, protected family care or medical leave status, race, religion (including beliefs and practices or the absence thereof), sexual orientation, military or veteran status, or any other characteristic protected by
Additional details
- Our mission at Oura is to empower every person to own their inner potential.
- We've helped millions of people understand and improve their health by providing daily insights and practical steps to inspire healthy lifestyles.
- Empowering the world starts with living our values and empowering our team.
- As a quickly growing company focused on helping people live healthier and happier lives, we ensure that our team members have what they need to do their best work — both in and out of the office.
- Oura’s engineering organization consists of talented developers distributed across the EU and US. For day-to-day feature work, our engineers are organized into smaller cross-functional teams.
- Our teams have a great deal of autonomy and are responsible for the design, development and architecture of their features.
- Teams take full ownership of their code and handle everything from concepting, design and implementation to release, maintenance and bug fixes. About the role
- Work with rich longitudinal signals from wearables plus real-world context.
- Balance scientific depth, engineering pragmatism, and product impact so millions of members get guidance that respects both their biology and their real lives.
- This role is ideal for someone who wants to work end-to-end - from problem framing and model/tooling choices to productionization, evaluation, and iteration - across both product-facing experiences and backend systems, in a domain where outcomes and behavior change, not clicks, are the primary success metrics. What you will do