Tech Lead, Applied AI

About the role

Abby Care is building the leading AI-native platform for family-led care at home for all of America. The role involves owning the technical direction and delivery of a major Applied AI problem area within the Abby Care platform. You will lead a team of engineers responsible for building production systems that automate complex healthcare workflows. Depending on the area of ownership, these systems may determine intake qualification, interpret clinical documents, prepare prior authorization packets, assist caregivers and clinicians, coordinate operational work, or identify cases requiring human judgment. This is a senior individual-contributor leadership position where you will set technical direction, lead execution, mentor engineers, and remain deeply hands-on in architecture and implementation. You will partner closely with Product, Clinical, Operations, Analytics, and platform teams to ensure AI systems are reliable, compliant, and impactful. This role offers the opportunity to solve one of the most important challenges of our time by transforming family care at scale.

Key facts

What you'll do

• Own the technical strategy and roadmap for a major Applied AI domain within the Abby Care platform.
• Translate ambiguous healthcare and operational problems into production-ready AI systems that meet clinical and business needs.
• Architect and build agentic systems that reason over complex information, use internal tools, and execute workflows end to end with reliability.
• Lead engineers through system design, implementation, evaluation, launch, and continuous iteration in a fast-paced environment.
• Establish human-in-the-loop controls based on confidence, risk, reversibility, and regulatory requirements to ensure safe deployment.
• Build reusable capabilities for retrieval, orchestration, tool use, structured outputs, tracing, and feedback to accelerate future development.
• Define evaluation datasets, quality metrics, release thresholds, and production monitoring to measure the impact of AI systems.
• Partner closely with Product, Clinical, Operations, Analytics, and platform teams to align on priorities and integration points.
• Mentor senior and junior engineers and raise the technical bar across the Applied AI organization through code reviews and design discussions.
• Contribute directly to architecture, prototyping, code, and critical production systems to unblock high-priority initiatives.
• Evaluate and benchmark third-party models and components to select the best-fit technologies for healthcare use cases.
• Drive standards for data quality, labeling, and governance to ensure robust and compliant AI workflows.
• Collaborate with Compliance and Legal to implement controls that meet healthcare regulations and operational policies.
• Analyze production telemetry to identify failure modes and drive improvements in system performance and user experience.

Requirements

• 8+ years of experience in software engineering, machine learning, or Applied AI across relevant domains and technologies.
• Demonstrated experience technically leading the delivery of AI-powered products or platforms from conception through production.
• Strong hands-on experience with language models, agent architectures, retrieval, tool use, structured outputs, and evaluation methodologies.
• Experience building systems over complex, incomplete, or unstructured real-world data while maintaining reliability and performance.
• Strong software engineering and system-design fundamentals, including backend systems, APIs, distributed systems, and data modeling.
• Experience defining evaluation methodologies and production monitoring for probabilistic and risk-sensitive AI systems.
• Experience leading technical projects and mentoring engineers to achieve high-quality outcomes under tight deadlines.
• Strong product judgment and ability to move from ambiguous problems to measurable outcomes and clear execution plans.
• Excellent communication and cross-functional collaboration skills to work effectively with clinical, product, and engineering stakeholders.
• Must reside in or be willing to relocate to the San Francisco Bay Area to align with team collaboration and regulatory expectations.

Nice to have

• Experience with fine-tuning, post-training, reinforcement learning, synthetic data, knowledge graphs, workflow engines, or state machines.
• Experience in healthcare, fintech, or other regulated industries where compliance and risk management are critical.
• Experience with advanced evaluation techniques for agentic systems, including traceability and explainability.
• Familiarity with healthcare workflows, payer processes, or prior authorization systems.
• Experience building and operating retrieval-augmented generation systems and tool-use frameworks.
• Contributions to open-source projects or technical publications that demonstrate thought leadership in Applied AI.

Practical notes

This is a full-time hybrid role based in San Francisco, with four days per week in person.