Principal AI Engineer, Arine

• 10+ years of experience in machine learning, AI systems, or data-driven backend engineering
• Expertise in building production-grade ML systems or intelligent decision engines
• Deep understanding of how to blend models, business rules, and structured data to power real-world workflows
• Strong Python engineering skills and familiarity with ML frameworks and modern data tools (e.g., PyTorch, scikit-learn, Airflow, SQL, AWS)
• Proven ability to drive complex technical initiatives end-to-end: from scoping and design through implementation and iteration
• Track record of influencing engineering and product strategy through deep technical leadership
• Excellent communication skills and ability to navigate ambiguity with curiosity and pragmatism
• Ability to pass a background check
• Must live in and be eligible to work in the United States

Desirable

• We’re hiring a Principal AI Engineer to lead the evolution of Arine’s decision intelligence systems
• In this role, you’ll serve as a key architect and hands-on technical leader, driving the design, implementation, and refinement of AI-powered systems that support real-time, personalized decision-making
• You’ll partner closely with AI leadership, product managers, clinicians, and engineers to shape the long-term architecture of our platform and deliver systems that are scalable, resilient, and aligned with our mission
• This is a high-impact role for someone who excels at navigating complexity, bridging ML and systems thinking, and influencing teams through deep technical insight and collaboration
• Own the architecture and technical roadmap for Arine’s next-generation AI decision systems
• Design and implement scalable, intelligent frameworks that blend ML models, rules, and data-driven logic
• Lead technical design discussions, make high-stakes tradeoffs, and drive execution across multiple teams
• Collaborate with stakeholders across engineering, data science, clinical, and product to ensure solutions are clinically meaningful and technically sound
• Ship reliable, maintainable code that integrates AI into operational workflows at scale
• Set and evolve best practices around AI system design, observability, model integration, and governance
• Mentor senior engineers and help grow technical excellence across the AI team