Clinical Informatics Specialist
AI Summary
A Clinical Informatics Specialist analyzes and reviews AI-generated medication content, creates clinical training datasets, and serves as a pharmacy SME to ensure AI outputs are accurate, safe, and aligned with real-world practice.
About this role
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 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.
Skills
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