Applied AI Engineer

Reporting to the Director, Applied AI, you will work on practical, high-impact problems such as collecting and interpreting clinical documents, automating intake and prior authorization work, assisting caregivers and nurses, detecting operational or billing risks, and routing exceptions to the right person. You will contribute across the development lifecycle: understanding the underlying workflow, prototyping solutions, preparing datasets, building evaluations, implementing production systems, and learning from real-world usage.

What you’ll work on:

• Build AI-powered products and automation: Develop agents, copilots, and intelligent workflows that help caregivers, clinicians, and operational teams deliver better care at scale.
• Develop production systems: Build the backend services, APIs, data pipelines, integrations, and reusable AI components required to move solutions from prototype to reliable production use.
• Work with complex healthcare information: Create systems that extract, retrieve, and reason over clinical documents, conversations, operational records, and other structured and unstructured data.
• Evaluate and improve system quality: Build representative datasets, measure performance, analyze failures, and improve models, prompts, retrieval, tools, and workflow logic based on evidence.
• Learn directly from users and operations: Partner with Product, Design, Clinical, and Operations to understand real workflows, identify edge cases, and rapidly iterate based on production feedback.
• Contribute to strong engineering foundations: Write maintainable, well-tested code and help build shared capabilities for orchestration, tool use, structured outputs, monitoring, tracing, and evaluation.

What success looks like:

• You consistently ship AI-powered capabilities that solve real problems for caregivers, clinicians, and operational teams.
• Your work progresses from prototype to reliable production functionality rather than stopping at demonstration-stage experiments.
• The systems you build are supported by clear evaluations, monitoring, and documented limitations.
• You use production feedback and error analysis to improve system quality over time.
• You collaborate effectively with product engineers, domain experts, and operational users.
• You develop reusable components that accelerate future Applied AI work.
• You grow your ability to independently own increasingly complex projects and technical decisions.
• You build a strong understanding of when to use AI, deterministic software, or human review to produce the best outcome.

What you’ll have:

• 2+ years of professional software engineering, machine learning, or Applied AI experience, or equivalent demonstrated ability.
• Strong programming skills and software engineering fundamentals.
• Experience building applications using language models, machine-learning models, or modern AI APIs.
• Familiarity with backend development, APIs, data processing, testing, and production software systems.
• Ability to structure ambiguous problems, test assumptions, and iterate based on evidence.
• Interest in building evaluations and understanding why AI systems succeed or fail.
• Strong ownership, curiosity, and willingness to engage directly with users and operational workflows.
• Clear written and verbal communication skills.
• Must reside in or be willing to permanently relocate to the San Francisco Bay Area.
• Experience with Python, agent architectures, retrieval-augmented generation, document intelligence, multimodal models, structured generation, model evaluation, monitoring, or prompt optimization is preferred but not required.
• Experience in healthcare, fintech, insurance, another regulated environment, a startup, or an operations-intensive business is preferred but not required.