Senior Applied AI/ML Engineer

📋 Job Overview

Pivotal Health is the leading technology platform that helps healthcare providers get paid fairly in an increasingly complex reimbursement landscape. We are investing heavily in AI as a core strategic capability to transform healthcare operations. As a Senior Applied AI/ML Engineer, you will design, build, and improve production AI systems that solve complex healthcare and operational challenges.

🏢 About Pivotal Health

Pivotal Health combines software, data, and service into a seamlessly integrated, AI-driven platform that simplifies 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.

🎯 The Role

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.

✅ Key Responsibilities

• Own and improve production AI systems, designing, building, deploying, and optimizing AI/ML solutions that support critical healthcare products and operational workflows.
• Build LLM-powered applications, developing production systems involving large language models, retrieval, structured generation, tool use, orchestration, and agentic workflows.
• Develop intelligent workflow automation, creating AI-powered systems that automate complex, multistep processes and improve the speed, consistency, and quality of operational decision-making.
• Own solutions end-to-end, taking projects from problem definition and experimentation through development, deployment, monitoring, and ongoing optimization.
• Design evaluation and experimentation frameworks, creating testing methodologies, benchmarks, and feedback loops that improve model quality, system performance, reliability, and business outcomes.
• Translate business problems into scalable systems, partnering 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, improving prompts, retrieval strategies, model selection, system logic, and application performance through continuous experimentation.
• Build reliable AI infrastructure, contributing to the architecture, observability, testing, versioning, rollout safety, and operational reliability of AI-powered systems.
• Work with complex healthcare data, building solutions that operate effectively across structured and unstructured information while maintaining high standards for accuracy, privacy, security, and compliance.
• Accelerate AI adoption across the organization, applying AI tools and best practices to improve team productivity and help establish scalable, AI-native ways of working.
• Balance speed with rigor, delivering impactful systems quickly while maintaining high standards for quality, reliability, safety, and maintainability.

📌 Required Qualifications

• 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, machine learning, LLM-powered, or agentic systems in production.
• Strong software engineering background, particularly with Python and backend systems that support production-scale AI applications.
• Experience designing and interpreting experiments, evaluation frameworks, benchmarks, or performance measurement systems.
• Proven ability to translate complex operational requirements and real-world data into reliable, scalable, and shipped products.
• Understanding of production engineering practices, including testing, monitoring, observability, system reliability, and safe rollouts.
• Product-oriented mindset with the ability to navigate ambiguity, make thoughtful technical decisions, and drive initiatives from concept through deployment.
• Strong communication and collaboration skills, with the ability to partner effectively across engineering, product, data, and operational teams.

⭐ Desirable Experience

• Experience building AI-powered products in healthcare, insurance, financial services, or another regulated industry.
• Experience working with healthcare data, clinical documentation, insurance claims, or healthcare operational workflows.
• Familiarity with explainable AI and systems where accuracy, transparency, and compliance are critical.

🎁 Benefits

Salary: $180K – $230K • Offers Equity

🛂 Visa & Eligibility

Not specified