• Model Productionization: Lead the engineering efforts to take cutting-edge data science models from research and development to scalable, production-ready systems, ensuring robustness, performance, and reliability. • Agentic AI Development: Design, develop, and deploy intelligent AI agents and multi-agent systems using frameworks like Google ADK, LangChain, and LangGraph. These agents will automate complex clinical and administrative workflows, such as detecting missed HCC codes, surfacing quality gaps, prompting compliant CPT submissions, and automating patient outreach. • System Architecture: Contribute to the architectural design of our AI-driven operating system, focusing on modularity, scalability, and integration points for AI services within our broader platform. • MLOps & Infrastructure: Implement and champion MLOps best practices for continuous integration, deployment, monitoring, and optimization of AI models and agent behaviors in a real-time clinical environment. • Performance & Reliability: Ensure the high performance, low latency, and fault tolerance of AI agents and inference pipelines, critical for real-time decision support and automated actions. • Cross-Functional Collaboration: Work closely with data scientists, clinical domain experts, product managers, and other engineering teams to translate complex clinical problems into AI solutions and integrate them seamlessly into the Arbiter platform. • Mentorship & Innovation: Actively mentor junior AI engineers, contribute to our internal knowledge base, and stay abreast of the latest advancements in AI, machine learning, and agentic systems to continuously innovate our offerings. • Hiring & Onboarding: Participate in interviewing and onboarding new team members, helping to grow a world-class AI engineering organization.