Pharma AI Architect: Foundation Models & Data Strategy

Visa Hunt

United States

On-site

USD 126,000 - 350,000

Full time

14 days+

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Job summary

IQVIA is seeking an experienced AI Solutions Architect to lead the design and delivery of next-generation AI solutions for pharmaceutical and life sciences organizations. You will combine expertise in foundation models, knowledge graphs, agentic AI, and data architecture with strong consulting and client leadership skills to deliver measurable business value.

Lead the design and deployment of AI solutions across pharmaceutical R&D, leveraging foundation models and RAG techniques, and architect

Qualifications

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.

Responsibilities

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.
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.
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.
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.
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.
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.