Pharma AI/ML Engineer for Statistical Production

Summary

IQVIA is a global provider of clinical research services, commercial insights, and healthcare intelligence for the life sciences and healthcare industries. The Pharma AI/ML Engineer will design, develop, and deploy AI-enabled solutions for statistical programming, including generative AI workflows, RAG systems, modular services, reliability controls, and human-in-the-loop capabilities. The role will also support LLMOps and collaborate with technical, statistical programming, security, validation, and governance teams to transition proofs of concept into scalable enterprise solutions.

Responsibilities

• Design and develop AI-enabled solutions for Statistical Programming, contributing to a scalable, modular, secure, and reusable architecture across multiple studies and use cases
• Build end-to-end Generative AI and agentic workflows encompassing data and metadata ingestion, retrieval, reasoning, tool use, code generation, execution, validation, and human review
• Develop RAG and knowledge-driven solutions that integrate organizational standards, metadata, specifications, historical study assets, programming conventions, and other approved knowledge sources
• Develop modular AI services, APIs, and reusable components, appropriately separating deterministic business rules and standards from probabilistic AI/LLM-based reasoning and generation
• Implement controls for AI reliability, reproducibility, and quality, including structured inputs/outputs, prompt and model versioning, validation rules, automated evaluation, regression testing, and quality checks of AI-generated artifacts
• Build traceability and human-in-the-loop capabilities supporting review, approval, feedback, exception handling, audit trails, and lineage from source information and retrieved context through generated outputs
• Support deployment and LLMOps practices across development, testing, validation, and production environments, including Git/CI/CD, monitoring, logging, model and prompt lifecycle management, security, and performance/cost optimization
• Collaborate with Statistical Programming, Enterprise Architecture, IT/Cloud, Security, Validation, and Governance teams to transition AI proofs of concept into scalable enterprise solutions while evaluating emerging AI technologies and architectural patterns
• Other duties as assigned

Skills

• Bachelor's or master's degree in computer science, Engineering, Artificial Intelligence, Data Science
• 2+ years of hands-on experience in software engineering, AI/ML engineering, data engineering, or related technical roles, with demonstrated experience building and deploying production-quality applications
• Hands-on experience developing Generative AI/LLM solutions, with knowledge of RAG, prompt/context engineering, embeddings, vector search, structured outputs, tool/function calling, and agentic AI workflows
• Strong programming skills in Python and experience with modern software engineering practices, including modular design, APIs, Git, automated testing, CI/CD, and preferably containerized/cloud-based applications
• Experience working with AWS and familiarity with cloud-based AI/ML services, data storage, security/access controls, logging, and monitoring
• Understanding of AI reliability and evaluation concepts, including reproducibility, hallucination mitigation, validation, prompt/model versioning, automated evaluation, regression testing, traceability, and human-in-the-loop approaches
• Strong analytical and problem-solving skills with the ability to work across technical and business teams; experience in pharmaceutical/biotechnology or regulated environments and familiarity with clinical data, Statistical Programming, SAS/R, CDISC/SDTM/ADaM, or GxP principles is preferred but not required
• Good communication and organizational skills required

Qualifications

Must Haves

• Bachelor's or master's degree in computer science, Engineering, Artificial Intelligence, Data Science
• 2+ years of hands-on experience in software engineering, AI/ML engineering, data engineering, or related technical roles, with demonstrated experience building and deploying production-quality applications
• Hands-on experience developing Generative AI/LLM solutions, with knowledge of RAG, prompt/context engineering, embeddings, vector search, structured outputs, tool/function calling, and agentic AI workflows
• Strong programming skills in Python and experience with modern software engineering practices, including modular design, APIs, Git, automated testing, CI/CD, and preferably containerized/cloud-based applications
• Experience working with AWS and familiarity with cloud-based AI/ML services, data storage, security/access controls, logging, and monitoring
• Understanding of AI reliability and evaluation concepts, including reproducibility, hallucination mitigation, validation, prompt/model versioning, automated evaluation, regression testing, traceability, and human-in-the-loop approaches
• Strong analytical and problem-solving skills with the ability to work across technical and business teams; experience in pharmaceutical/biotechnology or regulated environments and familiarity with clinical data, Statistical Programming, SAS/R, CDISC/SDTM/ADaM, or GxP principles is preferred but not required
• Good communication and organizational skills required

Benefits

• Remote work arrangement
• A range of health and welfare and/or other benefits