Role overview
Arbiter is reimagining how healthcare works - not by adding more point solutions, but by building the infrastructure that runs the system. We’re designing the intelligent operating spine that unifies data, automates workflows, and aligns incentives across providers, payers, and patients. Our platform embeds AI into real-world care and revenue cycle operations, transforming administrative chaos into orchestrated execution.
We’ve just closed one of the largest early-stage raises in health tech history - backed by some of the most influential players in the industry who collectively manage millions of lives and billions in spend. Paired with a powerhouse board and executive team, we have the capital, context, and relationships to move quicker than anyone - tackling the problems we know intimately and scaling what works. Our MVP is already live with hundreds of providers managing hundreds of thousands of lives, and improving daily based on real-world feedback.
At Arbiter, engineers don’t just ship features - they shape the foundation of an industry in flux. You’ll work alongside a small, elite team of product leaders and technologists from FAANG and top startup and healthcare orgs to architect systems that handle millions of patient records, build AI agents that execute critical healthcare workflows, and design platforms that major health entities depend on daily. Every line of code you write shapes how a $4T industry operates.
What you'll work on
As a Senior AI Engineer, Prior Authorization, you will be instrumental in bringing our advanced data science models to life and building sophisticated agentic AI systems for the clinical domain:
- 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 streamlining provider-facing prior authorization, 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 and into existing partner workflows (e.g., EHRs).
- 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 that augment and work lock-step with expert human reviewers, 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.
What we're looking for
- Familiarity with Google ADK for AI development and deployment.
- Direct experience working with Large Language Models (LLMs) and their application in real-world systems.
- Knowledge of MLOps principles, including CI/CD for ML, model monitoring, versioning, and explainability.
- Proven track record of building semi-autonomous AI systems that augment expert users (e.g., human-in-the-loop for clinical review) and embed natively into their workflows.
- Experience with unstructured data processing (e.g., natural language processing for clinical notes), including the use of sentence transformer embedding models.
- Contributions to open-source AI/ML projects or relevant publications.
This role can be remote or onsite, based in our New York City or Boca Raton offices, in a fast-paced, collaborative environment where great ideas move quickly from whiteboard to production.