Distinguished AI Engineer

Job Description

Distinguished AI Engineer

Company: Charlie Health

Location: New York, NY (Hybrid)

Work Arrangement: 4 days/week in-office (NYC), within 75 minutes commuting distance

Compensation

• Base Salary: $350,000 - $600,000 per year
• Additional: Stock options and other benefits included

Role Summary

Charlie Health is seeking a Distinguished AI Engineer to lead the design, development, and deployment of agentic AI systems. This hands-on technical leadership role will focus on building multi-agent architectures grounded in real-time clinical signals to replace brittle human handoffs with auditable, supervised AI workflows for scheduling, intake, insurance verification, and care coordination.

Key Responsibilities

• Technical Ownership: Serve as the technical owner of agentic AI, overseeing architecture, model strategy, production deployment, and reliability.
• Clinical Operations Agents: Design systems that handle scheduling, intake, insurance verification, referral triage, and care coordination.
• Clinician Copilots: Develop tools for real-time documentation, risk surfacing, and treatment-plan support integrated with EHRs.
• Agentic Substrate: Build eval frameworks, observability tools, guardrails, tool registries, and PHI-safe logging environments.
• Model Strategy: Define strategy across frontier models, fine-tunes, and classic ML for executive and clinical leadership.
• Collaboration: Partner with Product, Clinical, and Data teams to identify AI opportunities in patient and operational experiences.
• Best Practices: Establish standards for AI reliability, safety, evaluation, and explainability in a regulated clinical environment.
• Leadership: Mentor engineers and data scientists while fostering a culture of technical excellence.

Requirements

• Experience: 10+ years of software engineering experience, with recent years focused on LLM/ML-powered systems in production.
• Technical Skills: Hands-on experience designing agentic systems, including tool use, planning, multi-agent orchestration, eval design, and failure-mode analysis.
• Leadership: Track record of owning complex technical initiatives end-to-end (evaluation infrastructure, observability, on-call, compliance).
• Communication: Strong skills bridging executive strategy conversations and engineering code review.
• Domain Interest: Genuine interest in healthcare and applying AI responsibly in regulated, high-stakes domains.
• Education: BS, MS, or PhD in Computer Science, Machine Learning, Engineering, Mathematics, or equivalent practical experience.
• Location: Must be able to work a hybrid schedule (4 days/week) in the NYC office.

Work Environment & Tech Stack

• Data Infrastructure: Snowflake, dbt, pgvector, and an emerging Intelligence Layer.
• Scale: National virtual Intensive Outpatient Program (IOP) serving patients across 41 states.
• Focus Areas: Clinical documentation, referral-source conversion, scheduling intelligence, and clinician productivity.