Senior Applied AI/ML Engineer

ABOUT PIVOTAL HEALTH Pivotal Health is the leading technology platform that helps healthcare providers get paid fairly in an increasingly complex reimbursement landscape. Today, many providers face persistent underpayment from health insurance companies, despite delivering high-quality care. While processes like IDR (Independent Dispute Resolution) were designed to promote fairness, they’re often administrative-heavy, time-consuming, and difficult to navigate without the right tools. Pivotal Health combines software, data, and service into a seamlessly integrated, AI-driven platform that simplifies these complex reimbursement workflows. We help providers efficiently dispute underpaid claims, reduce administrative burden, and recover the reimbursement they’re entitled to; without adding more work to already stretched teams. Our full-service IDR solution is just the starting point. We’re building solutions that enable providers to operate with clarity, control, and confidence across the reimbursement journey. ABOUT THE ROLE Pivotal Health is investing heavily in AI as a core strategic capability to transform healthcare operations. We are building intelligent systems that automate complex workflows, improve decision-making, and drive measurable business outcomes across the organization. As a Senior Applied AI/ML Engineer, you will design, build, and improve production AI systems that solve complex healthcare and operational challenges. You will work at the intersection of machine learning, software engineering, product development, and business operations to deliver scalable AI-powered solutions. This is an applied AI engineering role—not research in isolation. You will own systems end-to-end, from experimentation and model development through deployment, evaluation, monitoring, and continuous improvement. Your work will directly influence critical products, workflows, and business decisions across Pivotal Health. We are looking for product-oriented engineers who thrive in ambiguous environments, move quickly from ideas to execution, and are excited to build AI systems that create measurable impact. Whether your background is rooted in machine learning engineering, LLM applications, agentic systems, or intelligent workflow automation, success in this role requires strong technical judgment, a bias toward shipping, and a commitment to continuous improvement. WHAT YOU'LL DO Own and improve production AI systems. Design, build, deploy, and optimize AI/ML solutions that support critical healthcare products and operational workflows. Build LLM-powered applications. Develop production systems involving large language models, retrieval, structured generation, tool use, orchestration, and agentic workflows. Develop intelligent workflow automation. Create AI-powered systems that automate complex, multistep processes and improve the speed, consistency, and quality of operational decision-making. Own solutions end-to-end. Take projects from problem definition and experimentation through development, deployment, monitoring, and ongoing optimization. Design evaluation and experimentation frameworks. Create testing methodologies, benchmarks, and feedback loops that improve model quality, system performance, reliability, and business outcomes. Translate business problems into scalable systems. Partner with product, operations, data, and engineering teams to define success metrics and turn complex requirements into production-ready AI solutions. Optimize model and workflow behavior. Improve prompts, retrieval strategies, model selection, system logic, and application performance through continuous experimentation. Build reliable AI infrastructure. Contribute to the architecture, observability, testing, versioning, rollout safety, and operational reliability of AI-powered systems. Work with complex healthcare data. Build solutions that operate effectively across structured and unstructured information while maintaining high standards for accurac…