Clinical Quality AI Specialist - MD/DO
Team: Clinical Strategy and Services
Location: Remote
Commitment: Full-Time
Workplace Type: remote
Responsibilities
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Lead pre-deployment validation
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Produce model cards/transparency (intended use, limits, monitoring, rollback).
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Partner on data quality (provenance, representativeness, refresh cadence, privacy).
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Build LLM evaluation datasets/gold standards; run clinical red-teams and prompt testing; refine prompts/guardrails; assess RAG fidelity.
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Train clinicians to oversee AI tools and adjudicate exceptions; create SOPs/checklists/escalations for LLM use.
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Collaborate with engineering and product, security, compliance, legal, care and service line leaders.
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Administer clinical AI governance (ethics, safety, regulatory, privacy, change control, documentation) in partnership with the Patient Safety Officer
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Define clinical use criteria and human-in-the-loop guardrails;
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Maintain governance artifacts (charter, SOPs, decision logs) and audit readiness.
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Support clinical QA; URAC/NCQA activities; policy/standards/rubrics management.
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Lead/participate in event detection, RCA/FMEA, CAPA; education (CME/CE, targeted training).
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Support client/payer audits, RFPs, VBC metrics (HEDIS, MIPS), implementations, and escalations, grievances/appeals.
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Lead and/or support cross-functional efforts to analyze clinical quality performance data, identify improvement opportunities, and translate value-based care insights into health plan design enhancements that optimize outcomes, member experience, and cost efficiency.
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Conduct ongoing assessments of clinical services, applying continuous improvement and evidence-based methodologies to ensure service effectiveness, measurable patient outcomes, and alignment with organizational quality standards.
AI clinical tool validation and LLM strengthening
Clinical-in-the-loop enablement
AI governance and policy
Quality and patient safety
Qualifications
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MD/DO with active, unrestricted license.
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3+ years clinical practice; 2+ years in quality, patient safety, or clinical operations.
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Experience with clinical review of LLM outputs; building eval datasets; red-teaming/prompt testing; RAG assessment.
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QI/patient safety expertise (PDSA, Lean/Six Sigma, RCA/RCA2, FMEA, CAPA).
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Working knowledge of URAC, NCQA, CMS; familiarity with HEDIS/MIPS.
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Proven track record of quality improvement within value-based care models.
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Experience partnering with analytics/data science; interpret core performance metrics
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Excellent documentation and stakeholder communication.
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Experience building, deploying, and iterating, clinical AI agents
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Proficiency in business intelligence and analytics. (e.g., Tableau/Power BI; basic SQL/statistics).
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Experience in virtual care/care navigation and enterprise audits.
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Strong clinical judgment; systems thinking.
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Analytical rigor; documentation excellence.
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Risk identification/mitigation in tech-enabled care.
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Coaching/influencing across clinical and technical teams.
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Leads through ambiguity; works independently.
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Remote-first; limited travel (~10-15%)
- This is a remote role; however, candidates based in or near the San Francisco Bay Area are preferred.
Required
Preferred
Core competencies
Other
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