Ōura - Staff AI Engineer, Developer Productivity
Requirements
• We'd love to hear from you if you are: • An experienced builder: Building and operating production systems that other engineers depend on, including developer tooling, internal platforms, or AI infrastructure at scale. We weigh demonstrated outcomes over years. • Proven with agentic loops in production: You have built and operated agentic coding workflows or autonomous loops in a real engineering organization, beyond demos: background agents producing PRs, automated review, CI repair, test generation, or similar, with adoption and measured results. • Proven with agentic loops in production: • A whole-lifecycle thinker: You reason about specification, review, testing, CI/CD, release and operations as one system, and you know where the bottleneck moves when code generation gets cheap. • A whole-lifecycle thinker: • A technical leader: You set direction across teams you don't manage, write the designs others build on, and are trusted with the hard calls on architecture and risk. • A technical leader: • Strong on fundamentals: mobile domain or backend APIs, concurrency, distributed systems, testing, debugging and reliability. You treat AI output as a draft and can show how you verify it. • Strong on fundamentals: • Technically versatile: Fluency in one domain of backend, iOS, or Android, with a stretch into others. You use the tools available to work across platforms and pick up new stacks quickly. • Technically versatile: • Security and privacy conscious: You understand the responsibility of handling sensitive personal data and of giving agents access to real systems, and you design for both from the start. • Security and privacy conscious: • High agency: You thrive in ambiguity and shape the requirements yourself through experimentation. • High agency: • Collaborative and resilient: You bring teams along, take feedback from engineers who are skeptical, share credit, and keep going when experiments fail or the tooling changes under you. You communicate clearly with engineers, managers and non-engineering partners. • Collaborative and resilient: • Would be a benefit • Would be a benefit • You don't need all of these, but they're nice signals of fit: • Experience with coding agents at depth: skills, MCP servers, hooks, sub-agent orchestration, headless runs. • Built evaluation harnesses or benchmarks for coding agents, or LLM-as-judge grading tied to build and test outcomes. • Experience with sandboxed execution at scale: ephemeral dev environments, VM or container fleets, macOS build infrastructure. • Background in developer productivity measurement (DORA, SPACE, DX Core 4) and in turning metrics into decisions without turning them into targets. • Shipped to mobile apps or other environments with slow, expensive feedback loops. • Experience in digital health, wearables, MedTech, or other privacy-sensitive or regulated products. • Contributions to open-source AI projects, or a portfolio of projects built on the latest agent capabilities. • Mentored engineers or led an engineering community of practice.
Responsibilities
• You don't need to do all of these on day one, but these are the kinds of problems you'll own: • Set the technical direction for the agentic pipeline: Make our existing ticket-to-PR pipeline dependable infrastructure. Own its architecture, including agent orchestration, context management and tool calling, and improve its reliability, throughput, cost and developer experience across mobile, backend and web repositories. Run it unattended where the risk allows. • Set the technical direction for the agentic pipeline: • Close the loop across the SDLC: Extend agentic workflows beyond code generation into spec quality checks, test generation, automated review, CI failure triage and repair, release verification, and post-deploy signals, so the system improves from what happens after merge. • Close the loop across the SDLC: • Prototype fast, then harden: Get a new workflow running in days, prove it on real tickets with real squads, and turn what holds up into production infrastructure. • Prototype fast, then harden: • Run AI in production properly: Agents in production take more than an API call. Own the eval sets, LLM-as-a-judge grading, versioning, tracing and dashboards that tell us whether a workflow change made things better, including the hardest case: a change that passes CI and is still wrong. Track the numbers that matter (merge rate, rework, time-to-signal, cost per change, escaped defects) and make them visible to engineers and leadership. • Run AI in production properly: • Make autonomy safe: Design sandboxing, permissions, human checkpoints and guardrails proportional to risk, with privacy by design as the default. Health data, security and infrastructure changes get stronger controls; low-risk, easily verified work runs hands-off. • Make autonomy safe: • Lead AI-native engineering by example: Set the bar for AI-augmented engineering across the organization. Show in your own work what a pipeline-first engineer ships, and raise the craft of the engineers around you. • Lead AI-native engineering by example: • Drive adoption with the teams: Embed with squads and their AI DRIs, find where the pipeline breaks on real work, fix the system rather than the single output, and turn what works into paved paths, skills, templates and docs other engineers can extend. • Drive adoption with the teams: • Partner cross-functionally: Work with platform, developer productivity, security and privacy, AI infrastructure, mobile and backend squads, product and design, and engineering leadership to make trade-offs explicit and keep everyone moving on one system instead of five parallel ones. • Partner cross-functionally:
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 and add to our benefits!What we offer: • Competitive salary • An Oura Ring of your own + employee discounts for friends & family • Flexible working hours and remote working arrangements • Amazing culture of collaborative and passionate coworkers • If this sounds like the next step for you, please send us your application and CV as soon as possible. • Oura is proud to be an equal opportunity workplace. We celebrate diversity and are committed to creating an inclusive environment for all employees. 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 federal, state, or local laws. We will not tolerate discrimination or harassment based on any of these characteristics. • We will work to ensure individuals with disabilities are provided reasonable accommodation to participate in the interview process, to perform essential job functions, and to receive other benefits and privileges of employment. • Disclaimer: Beware of fake job offers!We’ve been alerted to scammers posing as ŌURA recruiters, especially for remote roles. Please note: • Our jobs are listed only on the ŌURA Careers page and trusted job boards. • We will never ask for personal information like ID or payment for equipment upfront. • Official offers are sent through Docusign after a verbal offer, not via text or email. • Stay cautious and protect your personal details. • To all recruitment agencies: Oura does not accept agency resumes. Please do not forward resumes to our jobs alias, Oura employees, or any other organization's location. Oura is not responsible for any fees related to unsolicited resumes.
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