Senior Applied AI Engineer, Position Statements

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 create measurable business impact across critical areas of the organization. From document understanding and workflow orchestration to next-generation decisioning systems, AI is becoming foundational to how we operate and scale.

As a Senior Applied AI/ML Engineer, you will design, build, and improve production AI systems that directly influence our most important business outcomes. Reporting to the Head of AI/ML Engineering, you will work at the intersection of software engineering, machine learning, and operational workflows to transform ambiguous business challenges into scalable, reliable solutions.

This role is focused on applied AI engineering-not research in isolation. You will own systems end-to-end, from problem definition and evaluation design to deployment and operational improvement. Your work will help establish how AI is adopted across the organization while ensuring the systems we build are production-ready, measurable, and impactful.

If you thrive in fast-moving environments, enjoy solving complex operational problems, and want to build AI systems that create tangible business value, this role offers the opportunity to shape a critical capability for the future of the company.

What You'll Do

• Own and improve production AI systems. Design, deploy, and optimize AI/ML solutions that support critical business workflows and operational decision-making.
• Build AI-powered workflow platforms. Develop and refine production workflows leveraging generative AI models, agent frameworks, orchestration systems, and decisioning engines.
• Design evaluation and experimentation frameworks. Create robust evaluation methodologies, testing strategies, and measurement systems that improve model quality, workflow performance, and business outcomes.
• Translate business problems into scalable systems. Partner with product, operations, and engineering teams to define success metrics and convert ambiguous requirements into production solutions.
• Optimize model and workflow performance. Improve prompts, retrieval strategies, agent behavior, and system-level workflows through continuous experimentation and feedback loops.
• Drive engineering excellence. Contribute to architecture, testing, observability, deployment safety, and operational reliability across AI-powered systems.
• Accelerate AI adoption across the organization. Leverage AI tools and best practices to improve team productivity while helping establish scalable AI-native ways of working.

Who You Are

• 5-8+ years of experience building software systems in production environments, with a strong track record of owning and delivering complex technical solutions.
• Experience building and operating applied AI, LLM, agentic, or decisioning systems in production environments.
• Experience designing experiments, evaluation frameworks, optimization loops, or performance measurement systems.
• Strong software engineering background with Python and backend systems supporting production-scale AI applications.
• Proven ability to translate complex operational requirements and real-world data into reliable, shipped products.
• Experience working within healthcare or similarly complex operational domains.
• Product-oriented mindset with a bias toward ownership, execution, and delivering measurable outcomes.
• Comfortable navigating ambiguity and driving initiatives from concept through production deployment.
• Demonstrated ability to balance technical excellence with business impact.

Nice to Have

• Experience in domains such as marketplaces, pricing optimization, ad technology, credit decisioning, lending, revenue optimization, or operational analytics.
• Experience with retrieval systems, prompt engineering, structured generation, model routing, agent architectures, or tool-using AI systems.
• Familiarity with…