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.

We’re hiring a Senior Applied AI / ML Engineer to build and improve high‑impact AI systems that sit directly in important product and operational workflows.

This role reports to the Head of AI/ML Engineering and is designed for someone who wants to work on applied systems, not research in isolation. You’ll operate at the intersection of models, software, product workflows, and business outcomes. Depending on team needs and your strengths, you may work on areas like document generation, dynamic offer engines and other next‑generation decisioning systems.

We are looking for product‑oriented applied engineers who can move quickly, own meaningful surfaces, and turn ambiguous opportunities into shipped systems with measurable value. Some candidates may come from a classic ML engineering path. Others may come from data science‑heavy environments where experimentation, optimization, decisioning, or marketplace dynamics were central. We’re open to both, as long as you are excited to ship.

We also want someone who is AI‑first in their own work. The right person will use AI actively in engineering, analysis, iteration, debugging, and experimentation, and will help the team build a strong AI‑native way of working.

• Own and improve applied AI and ML systems that influence important business workflows.
• Build and refine production workflows around generation, decisioning, retrieval, evaluation, and orchestration.
• Work on concrete systems such as position statement generation, offer engine improvements, open negotiation agents, and configurable rules or decisioning systems.
• Design and run experiments that improve model quality, workflow quality, and business outcomes.
• Partner with product, operations, and engineering teammates to define success metrics and translate messy real‑world problems into buildable systems.
• Improve prompt, model, and workflow behavior through tight feedback loops and practical iteration.
• Contribute to the engineering quality of these systems, including instrumentation, testing, rollout safety, and operational visibility.
• Use AI as a force multiplier in your own work and help the team move faster by bringing strong AI‑native habits.
• Balance speed and rigor in an environment where shipping matters and iteration is constant.

In the first 6 to 12 months, strong outcomes in this role would include:

• making clear improvements to position statement generation, offer engine behavior, open negotiation workflows, or related AI systems
• designing and running high‑value experiments with real product or business impact
• reducing failure modes and increasing confidence in production AI workflows
• helping create stronger feedback loops between model behavior, operational workflows, and business outcomes
• becoming a trusted technical owner for an important applied AI surface
• contributing to a team culture that is both highly practical and highly capable with AI

• excited by applied AI and ML problems that sit close to product and business outcomes
• strong technically but not looking for a research‑only role detached from shipping
• can work across experimentation,…