AIML Engineer, Agentic AI COA Accelerator
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Overview
In this role, you will design, build, and optimize AI workflows that support COA strategy generation, evidence synthesis, and expert review. You will own the technical implementation of AI reasoning, retrieval-augmented generation, model orchestration, and evaluation pipelines for COA use cases. You'll integrate therapy area context, trial design considerations, and regulatory factors to produce evidence-backed recommendations. You'll collaborate with cross-functional teams to ensure scientifically credible, secure, and commercially useful AI solutions. This is a mission-driven opportunity to scale IQVIA's COA offerings with advanced AI in a regulated, patient-centered domain.
Responsabilidades
- Design and optimize AI capabilities for COA strategy generation and evidence synthesis
- Own AI reasoning, retrieval-augmented generation, and model orchestration implementations
- Build AI workflows considering therapy area, indication, trial design, and regulatory context
- Develop mechanisms to distinguish strong evidence from weaker or outdated information
- Create and maintain model evaluation frameworks for factuality, accuracy, and hallucination risk
- Document model behavior, assumptions, and governance; support demos and client-facing work
- Collaborate with COA scientists, data engineers, product managers, security, and legal stakeholders
- Contribute to AI governance for responsible use in clinical research and decision support
Requisitos principales
- Degree in computer science, machine learning, AI, data science, computational linguistics, biomedical informatics, bioinformatics, engineering, or related field
- Experience building AI/NLP/LLM applications in production
- Experience with retrieval-augmented generation, embeddings, vector databases, semantic search, prompt engineering, model evaluation, and LLM orchestration
- Strong Python skills and modern AI/ML framework familiarity
- Experience with unstructured scientific/clinical/regulatory data
- Ability to translate expert reasoning into technical solutions in nuanced domains
- Understanding of AI output quality risks and when human review is needed
- Excellent documentation and cross-functional collaboration skills
- Fluency in English
- Collaborative mindset
- Strong analytical judgment
- Effective communicator with non-technical stakeholders
- Retrieval-augmented generation
- Embeddings, vector databases (e.g., Pinecone, Weaviate, Milvus, Qdrant)
- Semantic search and hybrid search