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ŌURA күнделікті биометриялық деректерді денсаулық пен әл-ауқат туралы практикалық түсініктерге айналдыратын ақылды сақиналар мен денсаулық технологияларын әзірлейді. Oura Ring үздіксіз тағуға арналған жеңіл құрылғы арқылы ұйқы, жүрек соғу жиілігі, белсенділік және күйзеліс сияқты көрсеткіштерді бақылайды. Компания әйелдер денсаулығы, жүрек денсаулығы және жалпы әл-ауқат сияқты бағыттарда жеке денсаулық мониторингіне назар аударады, денсаулыққа бағытталған деректерді тұтынушыға ыңғайлы аппараттық және бағдарламалық жасақтамамен үйлестіреді. Жұмыс іздеушілер үшін ŌURA денсаулық технологиялары мен өндіріс тоғысындағы компания болып саналады: оның жұмысы адамдарға өз денсаулығын жақсырақ түсінуге көмектесетін өнімдерді әзірлеумен байланысты.
Staff AI Data Transformation Architect (Hybrid) at ŌURA
Lead ŌURA’s enterprise AI adoption across health data, product, engineering, science, and business teams. Build governance, tooling, Databricks and AWS platforms, and production LLM and RAG capabilities.
Америка Құрама Штаттары
Калифорния169 150 $ – 233 000 $ / жыл
АраласТолық жұмыс күніЖетекшіҚажетті Тіл: ағылшын тіліЖасанды интеллектСипаттама
- Own the Data AI enablement roadmap across data, product, engineering, science, and business functions.
- Develop repeatable AI adoption models supported by playbooks, shared tools, evaluation methods, and measurable outcomes.
- Create common terminology and assessment frameworks for evaluating AI opportunities.
- Guide build-versus-buy decisions, vendor strategy, and organization-wide AI technology investments.
- Manage the enterprise AI toolset, including Databricks data and access integration, multi-agent workflows, token controls, and trusted data foundations.
- Collaborate with Governance, Security, Privacy, and Legal teams to establish responsible-AI safeguards and auditable change processes.
- Improve AI spending efficiency through observability, productivity practices, reclamation programs, and usage analysis.
- Set the Data AI architecture strategy for Databricks and AWS environments operating at terabyte-to-petabyte scale.
- Lead machine-readable data contracts, vector architectures, RAG implementations, and enterprise context-plane components for production LLM reporting and agentic AI.
- Evaluate data readiness and coordinate remediation with analysts and engineers.
- Redesign workflows in partnership with functional leaders.
- Increase internal AI capability through training, practitioner communities, and self-service guidance.
- Expand successful pilots into standardized company-wide practices.
- Connect executive priorities with functional leaders and enabling teams.
- Align AI productivity initiatives with engineering and business-unit goals.
- Define operating standards for functional AI champions and AI-tool administrators.
- Represent Data AI enablement in cross-company forums and present adoption and impact metrics to leadership.
Талаптар
- At least 8 years of experience scaling AI data solutions, products, or technology adoption from pilots into sustained organization-wide practice with measurable results.
- Experience creating durable operating models, standard procedures, and measurement systems that remain effective beyond individual projects.
- A record of influencing senior leaders and building alignment around long-term technology investments.
- Strong technical understanding of LLMs and implementation patterns, with the judgment to distinguish practical value from hype.
- Hands-on administration of at least one enterprise AI productivity platform, such as Cursor, Claude, ChatGPT Enterprise, Glean, Gemini, coding assistants, or LLM API gateways, including user and group management and configuration troubleshooting.
- Regular use of LLM assistants and agents with appropriate judgment, validation, and verification.
- A practical, experience-based perspective on when to build versus buy technology.
- Experience with enterprise data platforms, including lakehouse environments using AI or LLMs.
- Practical knowledge of role-based access and permissions across multi-domain or multi-region environments.
- Experience working with Security, Privacy, and Legal teams to define and implement responsible-AI controls in regulated or health-sensitive settings.
- Ability to influence senior stakeholders and align R&D and business units without formal authority.
- Ability to create and maintain SOPs, playbooks, and training that nontechnical users and administrators can follow independently.
- Excellent written and verbal communication, from hands-on troubleshooting discussions to executive steering committees.
- Preferred: Databricks Certified Administrator or Databricks Certified Data Engineer certification.
- Preferred: Familiarity with data mesh principles and domain-oriented ownership models.
- Preferred: Experience supporting ML workflows with MLflow, Feature Store, or Databricks Model Serving.
- Preferred: Knowledge of dbt for data transformation and analytics engineering.
- Preferred: Cloud and AI token FinOps experience, including cost-allocation tags, budget alerts, and tiered-storage optimization.
- Preferred: Exposure to Databricks Lakehouse Federation or comparable cross-platform query federation approaches.
- Preferred: Previous experience serving as an AI champion or leading a similar transformation initiative.
- Preferred: Familiarity with scripting or configuration automation, such as Python, shell, or configuration-as-code, to reduce manual administration.
- Preferred: Experience in health technology, consumer health, wearables, or another regulated, high-trust sector.
- Preferred: Advanced experience designing production data architectures for LLM, RAG, and vector-based applications.
- Preferred: Experience with MLOps frameworks, Vertex AI, MLflow, and production AI/ML lifecycle management.
- Preferred: Ability to define data requirements for agentic AI and interactive self-service analytics systems.
- Work location must be in the United States; applicants living in Alaska, Delaware, Iowa, Mississippi, Nebraska, South Dakota, West Virginia, or Wisconsin are not considered.
Артықшылықтар
- Competitive compensation with salary and equity components
- Health, dental, vision, and mental health support
- An Ōura Ring, along with discounts for employees’ friends and family
- 20 days of paid time off, 13 paid holidays, and 8 flexible wellness days
- Paid sick leave and parental leave
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