Senior AI Engineer

Arbiter is the AI-powered care orchestration system that unites healthcare. Today, healthcare runs on $100B+ in fragmented point solutions that can't see the full picture. We replace them with a single intelligent system that sits on top of EMRs and existing workflows, unifies clinical, policy, and financial data, then automates the actions that close care gaps - starting with site-of-care optimization.

Backed by one of the largest seed rounds in health tech history and operators who bring the expertise and distribution to scale nationally, we're building the connected infrastructure healthcare should have had all along.

• Engineering Excellence: Taking immense pride in our technical craft and the products we build, treating both with utmost respect and care.
• Impact-Driven Development: Firmly committed to engineering high-quality, fault-tolerant, and highly scalable systems that evolve seamlessly with business needs, minimizing disruption.
• Collaboration Over Ego: Valuing exceptional work and groundbreaking ideas above all else. We seek talented individuals who are accustomed to working in a fast-paced environment and are driven to ship often to achieve significant impact.
• Continuous Growth: Fostering an environment of continuous learning, mentorship, and professional development, where you can deepen your expertise and grow your career.

• 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, Lang Chain, and Lang Graph. 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.

• 8+ years of deep, hands-on experience in AI Engineering, Machine Learning Engineering, MLOps, or a closely related field, with a strong focus on product ionizing models.
• Exceptional proficiency in Python for building complex AI systems and data pipelines.
• Demonstrated experience designing, building, and deploying AI agents and multi-agent systems using frameworks like Lang Chain, Lang Graph, or similar agent orchestration tools.
• Profound understanding and hands-on experience with cloud-native AI/ML platforms, especially Google Cloud Platform (GCP) services (e.g., Vertex AI, Big Query ML, Dataflow).
• Strong knowledge of MLOps principles, including CI/CD for ML, model monitoring, versioning, and explainability.
• Solid understanding of machine learning algorithms, model training, evaluation, and inference.
• Intimate knowledge of and ability to implement unit, integration, and functional testing strategies.
• Experience providing technical leadership and guidance, and thinking strategically and analytically to solve problems.
• Friendly communication skills and ability to work well in a diverse team setting.
• Demonstrated experience working with many cross-functional partners.
• Demonstrated experience leading a software product or component vision and delivery plan.

• Familiarity with Google ADK for AI development and deployment.
• Direct experience working with Large Language Models (LLMs) and their application in real-world systems.
• Experience in the healthcare, life sciences, or other highly regulated industries, especially with clinical data (EMRs, claims, patient outcomes).
• Proven track record of building autonomous or semi-autonomous AI systems that operate with human-in-the-loop oversight.
• Experience with unstructured data processing (e.g., natural…