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Pivotal Health is a healthcare technology platform that helps providers navigate complex insurance reimbursement workflows and dispute underpaid claims using AI-driven solutions. The company combines software, data, and services to simplify processes like Independent Dispute Resolution (IDR), reducing administrative burden while helping providers recover entitled reimbursement.
As a Senior Applied AI/ML Engineer, you will design, build, and improve production AI systems that solve complex healthcare and operational challenges. This is an applied engineering role focused on shipping real products, not research in isolation. You will own systems end-to-end: from problem definition and experimentation through model development, deployment, monitoring, and continuous improvement.
Key responsibilities include:
- Owning and optimizing production AI/ML systems that support critical healthcare products and workflows
- Building LLM-powered applications involving retrieval, structured generation, tool use, orchestration, and agentic workflows
- Developing intelligent workflow automation that improves speed, consistency, and decision-making quality
- Designing evaluation frameworks, benchmarks, and feedback loops to improve model quality and business outcomes
- Translating complex business and operational requirements into scalable, production-ready AI solutions
- Optimizing model behavior through prompt engineering, retrieval strategies, and continuous experimentation
- Contributing to AI infrastructure architecture, observability, testing, versioning, and operational reliability
- Working with structured and unstructured healthcare data while maintaining high standards for accuracy, privacy, security, and compliance
- Partnering across product, operations, data, and engineering teams to define success metrics and drive adoption
You bring 5–8+ years of experience building software systems in production, with a strong track record of owning complex technical solutions. You have hands-on experience building and operating applied AI, machine learning, LLM-powered, or agentic systems in production. Your background includes strong software engineering fundamentals (particularly Python and backend systems), experience designing experiments and evaluation frameworks, and proven ability to translate real-world requirements into reliable, shipped products. You understand production engineering practices including testing, monitoring, observability, and safe rollouts. You are product-oriented, comfortable navigating ambiguity, and skilled at collaborating across teams.
Extra credit: healthcare or regulated-industry AI experience, familiarity with healthcare data/claims/clinical workflows, knowledge of explainable AI and fairness/transparency concerns, or experience with model fine-tuning, embeddings, and vector databases.
