Lead AI Engineer, Biomedical & Vigilance Innovation Own and drive the development of production-grade AI platforms for pharmacovigilance and safety signal detection
Location: North Carolina, United States
About The Role
United Therapeutics is a biopharma company focusing on rare and cutting‑edge therapies.
We are seeking a Lead AI Engineer with a start‑up mindset to design, develop, and deploy advanced AI solutions that transform how biomedical insights are generated and how safety signals are detected, assessed, and acted upon. The role operates at the intersection of data science, software engineering, and medical safety, applying advanced analytics, machine learning, and automation to create scalable platforms that support proactive risk management and accelerate informed decision‑making across the product lifecycle.
Key Responsibilities
- Design, build, validate, and maintain machine learning, natural language processing, and generative AI solutions for biomedical and pharmacovigilance use cases.
- Develop tools that support adverse event intake, case triage, coding assistance, duplicate detection, signal prioritization, and trend analysis.
- Engineer predictive models to identify emerging risks, patient patterns, and operational bottlenecks.
- Translate complex scientific and business requirements into production‑ready AI applications.
- Own model definition, fine‑tuning, and optimization to ensure fit‑for‑purpose AI solutions for the UT patient safety business.
- Define and execute a bold technology strategy spanning global patient safety, embedding AI, machine learning, and agentic automation across day‑to‑day PV operations, analytics, and signal detection.
- Drive the architecture, development, and delivery of next‑generation platforms for pharmacovigilance AI initiatives.
- Integrate structured and unstructured data from safety databases, clinical systems, literature, real‑world evidence, and external repositories.
- Create staging schemas and mine diverse sources for hidden trends and meaningful insights.
- Build scalable pipelines for data ingestion, transformation, and quality control.
- Apply ontology mapping, terminology harmonization, and metadata strategies across MedDRA, WHO Drug, and related standards.
- Ensure robust data lineage, traceability, and audit readiness.
- Support modernization of pharmacovigilance and organovigilance systems through AI‑enabled automation and decision support tools.
- Improve case processing efficiency, medical review, and governance reporting via AI‑enabled solutions.
- Contribute to next‑generation surveillance models for novel modalities such as xenotransplantation, cell therapy, gene therapy, and organ‑based therapeutics.
- Develop AI‑enabled dashboards and visualization tools for rapid interpretation of safety trends.
- Ensure AI models and digital tools align with GxP, privacy, security, validation, and regulatory expectations.
- Support model governance including performance monitoring, unbiased detection, explainability (XAI), and change control.
- Maintain documentation for validation, testing, intended use, and lifecycle management.
- Collaborate with safety, clinical, regulatory, medical affairs, biostatistics, and IT teams.
- Provide technical guidance to analysts, data scientists, and business partners.
- Deliver validated AI solutions that create measurable gains in vigilance quality, speed, and insight generation.
- Improve detection and prioritization of safety signals through advanced analytics.
- Enhance case processing and review efficiency while preserving quality and compliance.
- Establish reliable, scalable biomedical data assets for future innovation.
- Maintain regulatory‑ready governance for AI‑enabled safety systems.
- Advance our leadership position in responsible AI for the future of medicine.
- Perform other duties as required.
Minimum Requirements
- Bachelor’s, Master’s, or PhD in computer science, engineering, applied mathematics, data science, biomedical engineering, bioinformatics, artificial intelligence, or related field, with the following experience: 8+ years with a Bachelor’s, 6+ years with a Master’s, or 2+ years post‑PhD.
- 5+ years of experience in AI engineering, machine learning, or advanced analytics within biopharma, healthcare, or regulated industries.
- 5+ years of hands‑on expertise in AI tools such as Python, R, MATLAB, TensorFlow, PyTorch, and cloud‑based ML platforms.
- Track record of deploying AI, machine learning, and data science solutions that deliver measurable outcomes in production environments.
- Entrepreneurial, transformation‑oriented mindset able to move from concept to execution quickly and lead technology‑driven change.
- Background in AI‑native product development, including agentic AI, LLM‑powered applications, autonomous systems, computer vision, or ML‑driven process optimization.
- Strong problem‑solving capability and ability to operate in complex matrixed environments.
- Deep fluency in cloud‑native engineering, platform architecture, and modern software development practices.
- Experience with external innovation strategies, academic partnerships, and emerging technology investments.
- Engineering mindset to build production‑grade, compliant, and scalable platforms, not just proof‑of‑concept demos.
- Excellent communication skills for conveying technical outputs to non‑technical stakeholders and senior leadership.
- Ability to learn scientific domains quickly and ask insightful questions to drive technology improvements in manufacturing timelines, quality, and cost.
Preferred Qualifications
- 5+ years of experience with NLP, LLMs, knowledge graphs, or biomedical text mining.
- Experience with safety systems such as Argus, ArisG, Veeva, or equivalent platforms.
- Knowledge of pharmacovigilance, clinical development, biomedical data, or healthcare regulations.
- Exposure to drugs, biologics, devices in the rare disease space or advanced therapeutics.
- Curiosity about and willingness to develop deep domain expertise in pharma automation workflows, advanced analytics, and risk‑identification methodologies.
- Hands‑on experience with pharmacokinetic (PK) / pharmacodynamic (PD) modeling and simulation applied to AI in pharmacovigilance.
- Familiarity with GVP, FDA, EMA, ICH, and data privacy frameworks.
Benefits
This position will be located at our Durham, NC office with a hybrid schedule of 4 days in office and the option to work 1 day each week from home. Eligible employees may participate in the Company’s comprehensive benefits suite, including medical, dental, vision, prescription coverage, employee wellness resources, savings plans (401k, ESPP), paid time off, paid parental leave, disability benefits, and more.
Equal Opportunity Employer
United Therapeutics Corporation is an Equal Opportunity Employer, including veterans and individuals with disabilities. We strive to engage the minds, hearts, and most spirited efforts of each employee. This is a stimulating place to work.