Distinguished AI Engineer

Charlie Health•New York, NY

7h•$350,000 - $600,000•Hybrid

About The Position

Charlie Health is seeking a Distinguished AI Engineer to lead the design, development, and deployment of agentic AI systems across their platform. This role is crucial for building the next generation of behavioral health technology, focusing on systems that can actively schedule, coordinate care, draft clinical documentation, and more. The company is investing in a multi-agent architecture grounded in a real-time clinical signal graph, with HIPAA-native infrastructure, aimed at improving patient outcomes in a national virtual IOP. This is a hands-on technical leadership position with significant cross-functional collaboration with Engineering, Product, Data, Clinical, and executive leadership.

Requirements

10+ years of software engineering experience, with several recent years focused on LLM- or ML-powered systems in production.
Hands-on experience designing and operating agentic systems, including tool use, planning, multi-agent orchestration, eval design, and failure-mode analysis.
Track record of owning a complex technical initiative end-to-end, including evaluation infrastructure, observability, on-call, and regulatory or compliance review.
Strong communication skills and comfort operating across registers, from executive strategy conversations to engineering code review.
Genuine interest in healthcare and in applying AI responsibly in a regulated, high-stakes domain.
BS, MS, or PhD in Computer Science, Machine Learning, Engineering, Mathematics, or a related technical field, or equivalent practical experience.
Able to work a hybrid schedule of 4 days/week in our NYC office and located within 75 minutes' commuting distance of the office

Responsibilities

Serve as the technical owner of agentic AI at Charlie Health, from architecture and model strategy through production deployment and ongoing reliability.
Lead the development of clinical operations agents that handle scheduling, intake, insurance verification, referral triage, and care coordination, replacing brittle human handoffs with auditable, supervised AI workflows.
Lead the development of clinician copilots for real-time documentation, risk surfacing, and treatment-plan support, integrated with our EHR and clinical data platform.
Define and build the agentic substrate: eval frameworks, observability, guardrails, tool registries, prompt and policy versioning, PHI-safe logging, and simulation environments.
Own the model strategy across frontier models, fine-tunes, distilled specialists, and classic ML, and articulate it clearly to executive and clinical leadership.
Partner with Product, Clinical, and Data teams to identify high-leverage opportunities for AI across patient and operational experiences.
Establish best practices around AI reliability, safety, evaluation, and explainability in a regulated clinical environment.
Mentor engineers and data scientists across the organization and help foster a strong culture of technical excellence and responsible AI innovation.