Senior Software Engineer, Agentic AI

Role overview Apply agentic AI and large language models to a virtual healthcare clinic where AI tools support patients and licensed physicians handle clinical decisions. The role leads complex AI initiatives end-to-end, from problem scoping with clinicians through dataset building, modeling, evaluation, and production deployment with monitoring and guardrails.

Responsibilities - Lead technical execution of complex AI initiatives, owning design and delivery within a product or technical domain in partnership with senior engineers. - Design, build, train, evaluate, and improve advanced machine learning and LLM-based systems for patient- and provider-facing products, including conversational AI, personalization, user understanding, clinical decision support, and chronic care management. - Scope problems with clinicians and product partners, build datasets and evaluations, iterate on modeling, and ship to production with appropriate monitoring and guardrails. - Develop robust evaluation frameworks spanning offline benchmarks, human-in-the-loop review, and online experiments to confirm models are safe, accurate, and improving. - Improve the underlying data pipelines, training and inference infrastructure, prompt and model management, and tooling for clinical reviewers. - Partner with clinicians, product, and engineering to translate medical and operational requirements into ML problems and ship measurable improvements.

Requirements - Senior-level experience leading complex AI or ML initiatives end-to-end. - Strong background designing and shipping LLM-based or advanced ML systems to production. - Ability to scope ambiguous problems with cross-functional partners and drive them to results. - Experience building evaluation frameworks, including offline benchmarks and human-in-the-loop review. - Skill in building or improving ML infrastructure such as data pipelines, training systems, or inference platforms. - Strong collaboration and communication across engineering, clinicians, and product.

Nice to have - Experience applying ML or LLMs in healthcare, life sciences, or another regulated, high-stakes domain. - Background in clinical NLP, medical knowledge representation, or working with electronic health record data. - Hands-on experience building agentic systems or tool-using LLMs in production. - Experience scaling ML infrastructure for a small, fast-moving team. - Track record of technical leadership across teams, mentoring, or publishing influential work.

Benefits and work setup - Compensation range of $175,000–$210,000 per year, plus meaningful equity and comprehensive benefits including medical, dental, and vision coverage; flexible spending plans; generous PTO, floating holidays, and parental leave; 401(k) with employer matching. Fully remote within the U.S. with reliable internet and a private home-office workspace; on-camera work may be required.