AI Solutions Architect (Remote)

IQVIA • Durham, NC

4d • Remote

About The Position

We are seeking an experienced AI Solutions Architect to lead the design and delivery of next-generation AI solutions for pharmaceutical and life sciences organizations. This individual will help clients transform scientific, clinical, and operational data into explainable, trustworthy, and scalable AI solutions that accelerate research and development, improve decision-making, and drive innovation across the drug development lifecycle. Role Overview As an AI Solutions Architect, you will combine your expertise in foundation models, knowledge graphs, agentic AI, and data architecture with strong consulting and client leadership skills. You will work closely with scientific, business, and technical stakeholders to design and deliver solutions that leverage next-generation AI capabilities and deliver measurable business value.

Requirements

• Master's degree or PhD in Computer Science, Bioinformatics, Computational Biology, Data Science, Engineering, or a related field.
• Significant experience delivering AI, data, analytics, or digital transformation solutions in life sciences or pharmaceutical organizations
• Demonstrated expertise in designing and deploying solutions leveraging foundation models, retrieval-augmented generation (RAG), agentic AI architectures, knowledge graphs, semantic technologies, vector databases, semantic search, machine learning, and predictive analytics
• Experience designing AI solution architectures supported by strong data architecture principles.
• Strong programming and solution development experience, particularly in Python and modern AI frameworks.
• Experience with cloud platforms such as Azure, AWS, or Google Cloud.
• Experience designing and deploying AI solutions in regulated environments.
• Ability to translate complex business and scientific questions into structured AI solution designs and implementation plans.
• Understanding of pharmaceutical R&D processes, including drug discovery, translational science, clinical development, safety, and regulatory approval.
• Excellent communication, presentation, and consulting skills.
• Ability to engage effectively with both executive stakeholders and highly technical teams.

Nice To Haves

• Experience designing and implementing biomedical knowledge graph solutions, including the integration of knowledge graphs with foundation models and agentic AI to support intelligent applications and scientific discovery.
• Familiarity with biomedical ontologies, standards, and scientific data management practices, including FAIR data principles and semantic interoperability.
• Experience establishing AI evaluation, validation, and governance frameworks, including benchmarking, human-in-the-loop review, and other quality assessment methodologies.
• Understanding of the end-to-end pharmaceutical value chain, including R&D, regulatory affairs, market access, medical affairs, commercial operations, and post-marketing functions.
• Experience leading client engagements and mentoring multidisciplinary technical teams.

Responsibilities

• AI Solution Architecture: Lead the design and delivery of AI solutions across pharmaceutical research and development, translating business and scientific challenges into scalable solutions with measurable outcomes
• Recommend appropriate architectures that align business objectives , data assets, and technology capabilities
• Foundation Models and Agentic AI: Design and implement solutions using foundation models, large language models (LLMs), retrieval-augmented generation (RAG), and agentic AI frameworks
• Define approaches for model selection, orchestration, grounding, prompt design, evaluation, validation, and production deployment
• Knowledge Graphs and Semantic Systems: Architect biomedical knowledge graphs, ontologies, and semantic data models that support scientific discovery, reasoning, and intelligent information retrieval
• Integrate knowledge graphs with foundation models to improve contextual understanding, explainability, and AI performance
• Data Strategy and Engineering: Lead data integration, harmonization, and governance efforts across scientific, clinical, and operational data sources
• Establish data foundations that support scalable, trustworthy, and AI-ready solutions
• Client Leadership and Consulting: Serve as a trusted advisor to business, scientific, and technical stakeholders, leading workshops and solution design sessions
• Communicate complex technical concepts to both executive and technical audiences, guiding clients from strategy through implementation
• Innovation and Capabilities Development: Stay current on advances in AI, foundation models, and knowledge graphs, bringing emerging capabilities into solutions
• Contribute to reusable methodologies, accelerators, and leading practices that scale AI delivery across engagements

Benefits

• health and welfare and/or other benefits

What This Job Offers

• Job Type: Full-time
• Career Level: Senior