We are building a new, high-velocity squad within our Health Intelligence organization. This team is tasked with moving from data and insights to action and orchestration. We are looking for engineers who dont just use AI as a feature, but who use AI as a fundamental building block of both the product they build and the way they write code.
This is a fast-moving, LLM-forward team. We prioritize rapid prototyping, iterative loops, and AI-native development. You will be part of a US-based pillar designed to operate with the speed of a startup while leveraging the deep data moats of a global health leader.
As a Staff Engineer on this team, you will architect the backend systems and web interfaces that bridge the gap between complex health data and real-world user utility. You will be responsible for building the connective tissue that allows AI models to interact with external APIs, communication protocols, and personalized data layers.
This is a hybrid/in office role reporting to our San Francisco location.
What You'll Do
Rapid Prototyping: Move from concept to production in days, not months. You'll build and validate new interaction layers that bring health intelligence to users where they already are.
AI Orchestration: Design and implement backend logic for LLM-based agents, focusing on reliability, context-window management, and tool-calling (agentic workflows).
Full-Stack Ownership: While backend-heavy, you are comfortable spinning up modern web frontends or jumping into native iOS or Android development to test user experiences and gather immediate feedback. You use the tools available to deploy solutions across platforms and aren't limited to a single stack.
AI-Native Development: You will be expected to lead the way in AI-augmented engineering-utilizing tools like Claude Code, Cursor, and automated refactoring to maintain a velocity that traditional teams cant match.
Systems Integration: Build secure, scalable integrations between our internal intelligence engine and third-party service providers.
Applied MLOps: You understand that AI in production is more than just an API call. You have experience with MLOps best practices, including model monitoring, evaluation frameworks (LLM-as-a-judge), versioning, and deploying scalable data pipelines that fuel RAG systems.
Requirements
We would love to consider you for this role if you are:
Bonus Points
Benefits
At Oura, we care about you and your well-being. Everyone here at Oura has a ring of their own and we are continually looking to improve employee health.
What we offer:
Oura takes a market-based approach to pay, which may vary depending on your location. US locations are categorized into tiers based on a cost of labor index for that geographic area. While most offers will be closer to the starting range, successful candidates pay will be determined based on job-related skills, experience, qualifications, work location, internal peer equity, and market conditions. These ranges may be modified in the future.
Salary Ranges
Region 1: $233,000- $267,000
Note on Location
We are not considering candidates residing in the following states: Alaska (AK), Delaware (DE), Iowa (IA), Mississippi (MS), Missouri (MO), Nebraska (NE), South Dakota (SD), Vermont (VT), West Virginia (WV), and Wisconsin (WI).