AI Engineer

• Design, develop, and deploy machine learning models and AI-powered applications
• Collaborate with cross-functional teams to identify and implement AI/ML solutions for client needs
• Build and maintain data pipelines, model training workflows, and inference systems
• Evaluate and integrate large language models (LLMs), generative AI tools, and emerging AI frameworks
• Monitor model performance, conduct testing, and iterate on improvements
• Document technical architectures, methodologies, and best practices
• Stay current with AI/ML research and translate advancements into practical applications

• Define and evolve enterprise AI architecture, standards, reference models and implementation guidelines to support consistent solution delivery across business functions
• Align AI initiatives to enterprise strategies, roadmaps, and business priorities
• Identify and prioritize AI opportunities that drive student success and operational efficiency
• Design scalable AI platforms and solutions across data, application, and technology domains
• Provide guidance on how AI, ML, and automation will improve current and future-state architectures
• Lead design and implementation of AI-powered solutions (e.g., LLMs, agents, automation, and analytics)
• Integrate AI capabilities with enterprise applications and data platforms
• Guide evaluation and selection of AI/ML models, frameworks, and vendors
• Establish reusable patterns, APIs, and integration approaches
• Establish governance practices covering model oversight, responsible AI usage, security controls, compliance expectations, and lifecycle management
• Establish AI governance, including responsible AI, security, privacy, and compliance (FERPA, HIPAA, GDPR)
• Establish lifecycle management practices (MLOps/LLMOps, model monitoring, drift detection, retraining)
• Implement performance, bias, and risk monitoring frameworks
• Ensure secure AI architecture (e.g., data protection, isolation, adversarial defense)
• Partner with business, product, data, and engineering teams to provide AI solutions
• Provide architectural guidance to architects and delivery teams
• Facilitate workshops, POCs, demos and AI adoption projects identifying viable opportunities where AI can be a positive differentiator
• Mentor teams on AI best practices, patterns, and frameworks

Enterprise AI Architect

• Use Claude Code to implement new features and functions within the platform
• Translate product requirements and design specs into clean, production-ready code
• Review and refine AI-generated code to ensure correctness, performance, and maintainability
• Leverage AI to write and update automated tests for all new functionality
• Participate in async code reviews and provide constructive feedback
• Ensure new features, APIs, and architectural decisions are documented as they are built
• Proactively identify technical debt or gaps and surface them to the team

AI Software Developer

AI Research Scientist

• Build, deploy, and maintain production-grade AI and ML pipelines, backend services, and infrastructure that support Oura's AI Advisor and custom model initiatives
• Design and implement evaluation systems and tooling to measure grounding, reliability, and actionability of LLM and agentic systems in production
• Develop and deploy agentic AI systems in production
• Lead initiatives end to end — from problem definition and research through deployment, monitoring, and iteration
• Partner with Product and Engineering teams to translate data-driven insights into shipped product features
• Build and optimize custom AI solutions through fine-tuning, knowledge distillation, and quantization
• Help build Oura as a leader in AI expertise and infrastructure
• Proactively identify opportunities to improve the product and bring your own ideas to the table

Senior AI Scientist