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Clinical Informatics Specialist

San Francisco💼 Full-time🗓 2026-07-21 → 2026-07-31

About Latent

Latent is building the clinical intelligence layer for healthcare AI. Our platform enables AI systems to reason safely and accurately over medications, clinical knowledge, and patient-specific context. We work closely with healthcare organizations and AI builders to ensure models behave in ways that are clinically sound, regulatory-aware, and trustworthy.

About the Role

Latent is seeking a Clinical Informatics Specialist to join our Engineering, Product, and Data (EPD) organization. This role sits directly within Product and is deeply embedded in product development.

The Clinical Specialist will play a critical role in data generation, annotation, and evaluation to improve Latent’s AI models, while also serving as a clinical subject matter expert (SME) to inform feature development, workflows, and internal tooling.

You will partner closely with product managers, engineers, and data scientists to ensure Latent’s products reflect real-world clinical practice and meet the highest standards of safety and accuracy.

What You’ll Do

AI Model Training & Evaluation

• Analyze and review AI-generated content related to medications, prescriptions, drug interactions, contraindications, and patient education for clinical accuracy and clarity.

• Generate, label, and curate high-quality training and evaluation datasets based on real-world pharmacy and medication-use scenarios.

• Provide structured clinical feedback to improve model performance, reasoning quality, and edge-case handling.

• Identify gaps in AI knowledge and propose targeted data or educational interventions to address them.

Product Development & Clinical SME Support

• Serve as a clinical subject matter expert for product and engineering teams during feature design and iteration.

• Collaborate with product managers to translate clinical workflows into scalable product features.

• Actively test Latent’s pharmacist and medication-focused tools, providing actionable feedback and proposing product enhancements.

Quality, Safety & Compliance

• Ensure AI outputs align with current clinical guidelines, pharmaceutical standards, and best practices.

• Help define and enforce internal quality standards for clinical content used in training and evaluation.

• Ensure all data generation and AI outputs adhere to regulatory, ethical, and privacy requirements relevant to pharmacy practice.

Cross-Functional Collaboration

• Partner with data scientists, ML engineers, and product managers to design clinically grounded training sets and evaluation frameworks.

• Communicate complex clinical concepts clearly through written documentation and internal discussions.

• Contribute to continuous improvement of Latent’s clinical intelligence processes and tooling.

What We’re Looking For

• Background in pharmacy practice, including formal training or certification as a Pharmacist or Pharmacy Technician, Physicians Assistant, Nurse Practitioner, Nurse or equivalent hands-on clinical experience.

• Demonstrated experience working with medications, prescriptions, drug interactions, and pharmacy workflows in real-world settings.

• Strong clinical judgment and attention to detail, with the ability to evaluate medication-related content for accuracy, safety, and clarity.

• Ability to translate real-world clinical scenarios into structured data, annotations, or written feedback.

• Excellent written and verbal communication skills, especially when explaining complex clinical concepts to non-clinical teammates.

• Comfort collaborating closely with product, engineering, and data science teams in a fast-paced environment.

• Passionate about healthcare access.

Nice to Have

• Familiarity with clinical guidelines, regulatory considerations, and patient safety frameworks.

• Familiarity with prior authorizations, 340B, and medication assistance programs.

• Prior experience with Epic and/or Cerner.

• Prior experience with data annotation, model evaluation, or quality assurance for AI systems.

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