Job Description
Why Charlie Health? Millions of people across the country are navigating mental health conditions, substance use disorders, and eating disorders, but too often, they’re met with barriers to care. From limited local options and long wait times to treatment that lacks personalization, behavioral healthcare can leave people feeling unseen and unsupported. Charlie Health exists to change that. Our mission is to connect the world to life-saving behavioral health treatment. We deliver personalized, virtual care rooted in connection—between clients and clinicians, care teams, loved ones, and the communities that support them. By focusing on people with complex needs, we’re expanding access to meaningful care and driving better outcomes from the comfort of home. As a rapidly growing organization, we're reaching more communities every day and building a team that’s redefining what behavioral health treatment can look like. If you're ready to use your skills to drive lasting change and help more people access the care they deserve, we’d love to meet you. About the role The next generation of behavioral health will be built on agentic AI — systems that don't just predict or summarize, but act: scheduling, coordinating care, drafting clinical documentation, surfacing risk, and orchestrating the hundreds of micro-decisions that today consume clinician and operator time. Charlie Health's ambition is to build the most advanced agentic systems in healthcare. We are investing in a multi-agent architecture grounded in a real-time clinical signal graph, governed by HIPAA-native infrastructure, and deployed against measurable patient outcomes in a national virtual IOP. We are hiring a Senior Principal AI Engineer to lead the design, development, and deployment of these systems across our platform. This is a hands-on technical leadership role with deep cross-functional reach into Engineering, Product, Data, Clinical, and executive leadership. 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. What you'll work with An executive team that has committed to an AI-native operating model and is funding it. An AI Guild of senior engineers, data scientists, and clinical operators piloting AI across the company today. A modern data foundation including Snowflake, dbt, pgvector, and an emerging Intelligence Layer that exposes patient and operational signals as first-class events. Live workstreams in clinical documentation, referral-source conversion modeling, scheduling intelligence, and clinician productivity. A national virtual IOP serving patients across 41 states, with the regulated data and outcome signal needed to train, evaluate, and improve real systems. Why this role is hard Behavioral health is one of the most demanding applied-AI environments. Patients are often in acute distress. The regulatory surface spans HIPAA, state-by-state telehealth and licensure law, and rising FDA scrutiny of clinical decision support. AI systems in this environment must be observable, reversible, and defensible to clinicians, to regulators, and to internal review. We are looking for an engineer who finds those constraints clarifying rather than limiting. 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 o