Physician AI Engineer

Counsel Health

. Own the full lifecycle of clinical and safety agents, from scoping and PRD writing through architecture, evaluation, implementation, review, and production launch .

Posted 10/7/2026full-timeRemote • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in clinical evaluation frameworks and the full lifecycle of clinical and safety agents, with a strong focus on building and implementing AI solutions in healthcare. Proven ability to bridge the gap between clinical practice and engineering, ensuring effective communication and collaboration.

Highest-signal resume keywords

MD Or DO DegreeClinical ExperienceLLM Production ExperienceOwnership Of Shipped ProductsPublished Research In Clinical AI

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Clinical Evaluation FrameworksAI Performance BenchmarkingPrototyping And TestingHistory-TakingDifferential DiagnosisTriageTreatment Planning

Soft Skills

Experimental MindsetAbility To Translate Clinical Nuance

Certifications & Qualifications

Board-Eligible Or Board-Certified Status

Industry Keywords

Clinical AILLM EvaluationsEarly-Stage Startup ExperienceEngineering Organization Experience

About the role

Key responsibilities & impact

Own the full lifecycle of clinical and safety agents, from scoping and PRD writing through architecture, evaluation, implementation, review, and production launch
Establish a clinical evaluation framework as the canonical quality bar for at least one agent
Ensure evaluations are testable and productionized for engineers and researchers
Improve Counsel AI components including history-taking, differential diagnosis, triage, and treatment planning
Benchmark AI performance against physicians using representative case sets
Learn the existing stack by reading code, running evaluations, and working with the clinical team
Identify and prioritize weaknesses in Counsel’s AI and safety systems
Shadow current workflows, select an agent or safety component, prototype it, obtain review, and ship it

Requirements

What you’ll need

MD, DO, or international equivalent, with residency training or 3+ years of clinical experience completed
Substantive, hands-on experience building with LLMs in production, beyond experimentation
Track record of ownership over shipped products in industry or startup settings
Board-eligible or board-certified status with meaningful active or recent clinical practice (strongly preferred)
Published research, open-source work, or public writing on clinical AI, LLM evaluations, or related areas (strongly preferred)
Experience embedded inside an engineering organization (strongly preferred)
Experience operating at an early-stage startup or founding one
Experimental mindset and willingness to prototype, test, and iterate
Ability to translate clinical nuance to engineers and technical tradeoffs to clinicians
Eligibility to complete U.S. employment verification through E-Verify

Benefits

Comp & perks

Remote work in the United States
E-Verify employment eligibility processing