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Abby Care is building an AI-native operating system for home care that manages the full lifecycle from caregiver and patient intake through care delivery, billing, and compliance. The company combines clinical oversight with an AI-powered platform to train, enable, and support family caregivers in delivering high-quality care at home, partnering with leading health plans, providers, and community organizations.
As a Senior Applied AI Engineer reporting to the Applied AI Leader, you will own major initiatives from initial problem definition through production deployment and measurable impact. You will design and build production AI systems that automate complex, consequential healthcare workflows. Depending on the problem, you may build agents that collect clinical documentation, interpret evidence across multiple records, prepare prior authorization packets, assist nurses during visits, identify billing risk, or coordinate operational follow-up.
You will determine how workflows should be decomposed, what context and tools an AI system needs, how its behavior should be evaluated, where deterministic controls are required, and when human intervention is necessary. You will work closely with product engineers, product managers, designers, clinicians, operators, and analysts to ensure systems reflect real-world workflows and produce meaningful outcomes.
Key responsibilities include: owning high-impact AI systems end to end from workflow discovery through production deployment; building reliable agents and copilots that reason over structured and unstructured data; engineering for real-world complexity by combining models, retrieval, rules, state machines, and human oversight; building rigorous evaluation and monitoring with representative datasets and systematic error analysis; integrating AI into complete workflows across product and operations; and raising the technical bar through reusable platform capabilities and mentorship.
Success means independently delivering complex Applied AI systems with measurable improvements in workflow completion, speed, quality, or operational capacity; systems that respond safely to uncertainty through confidence handling and escalation; AI capabilities integrated into end-to-end workflows; reusable components that improve organizational velocity; and technical leadership that helps other engineers make better decisions.
REQUIREMENTS:
- 5+ years of professional software engineering, machine learning, or Applied AI experience
- Experience building and operating AI- or machine-learning-powered systems in production
- Strong hands-on experience with language models, retrieval systems, structured generation, model APIs, or agent architectures
- Strong software engineering fundamentals including backend systems, APIs, data modeling, testing, and observability
- Experience designing evaluations and analyzing the behavior of probabilistic systems
- Demonstrated ability to take ownership of ambiguous, cross-functional problems and drive them through implementation and iteration
- Strong judgment about where AI is appropriate and where deterministic approaches or human review are required
- Ability to communicate complex technical concepts clearly to technical and nontechnical partners
- Experience mentoring engineers, leading technically complex projects, or influencing architectural decisions
- Must reside in or be willing to permanently relocate to the San Francisco Bay Area
PREFERRED:
- Experience with model fine-tuning, post-training, reinforcement learning, synthetic data generation, multimodal models, document intelligence, knowledge graphs, ontologies, workflow engines, or state machines
- Experience in healthcare, fintech, insurance, or another regulated and operations-intensive environment
