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.
Key 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
What We're Looking For
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.
Preferred Experience
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.
IQVIA is a leading global provider of clinical research services, commercial insights and healthcare intelligence to the life sciences and healthcare industries. We create intelligent connections to accelerate the development and commercialization of innovative medical treatments to help improve patient outcomes and population health worldwide. Learn more at https://jobs.iqvia.com
IQVIA is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other status protected by applicable law. https://jobs.iqvia.com/eoe
IQVIA is committed to integrity in our hiring process and maintains a zero tolerance policy for candidate fraud. All information and credentials submitted in your application must be truthful and complete. Any false statements, misrepresentations, or material omissions during the recruitment process will result in immediate disqualification of your application, or termination of employment if discovered later, in accordance with applicable law. We appreciate your honesty and professionalism.
The potential base pay range for this role, when annualized, is $125,800.00 - $350,300.00. The actual base pay offered may vary based on a number of factors including job-related qualifications such as knowledge, skills, education, and experience; location; and/or schedule (full or part-time). Dependent on the position offered, incentive plans, bonuses, and/or other forms of compensation may be offered, in addition to a range of health and welfare and/or other benefits.