Associate AI Engineer

Job Description Summary Our team is growing and seeking a motivated, early-career Associate AI Engineer to help build the AI solutions that support our Health Economics and HTA Team. Working under the guidance of senior engineers, the Associate AI Engineer will contribute to turning validated prototypes into production-grade AI tools, support the development of new prototypes with delivery teams, and help maintain the AI tools already in use. The role offers hands-on experience across the full lifecycle of AI solutions, from retrieval and data extraction to drafting and quality control, applied to deliverables such as systematic literature reviews and evidence synthesis reports. The Associate AI Engineer will work in an Agile team across geographies and functions and will build knowledge of the health economics and HTA domain on the job. REQUIRED KNOWLEDGE Solid foundations in Python and software engineering, and practical exposure to building applications with large language models (academic, personal or professional), are essential. The role requires curiosity, attention to detail and the willingness to learn complex, document-heavy workflows. Exposure to the healthcare sector or the pharmaceutical market is desirable. RESPONSIBILITIES Production Solutions Contribute to rebuilding validated prototypes as production agents on our enterprise AI development platform, under the guidance of senior engineers Implement components of reusable pipeline modules (retrieval, screening, data extraction, drafting and quality control) Write tests and evaluation scripts and follow enterprise engineering standards Prototyping Support the build and refinement of AI workflows together with delivery teams Support pilots on live projects and help measure the time saved Support Handle routine runs of AI tools already in use and document issues and fixes Write and maintain technical documentation and user guides Ways of Working Work in Agile sprints, managing tickets in Jira Raise merge requests for all changes and act on review feedback before anything ships QUALIFICATIONS, EXPERIENCE, TECHNICAL AND PERSONAL SKILLS Essential Qualifications Bachelor’s degree in Computer Science, Computer Engineering, Electrical and Computer Engineering, Software Engineering, Informatics, Information Technology or Data Science Essential Skills, Knowledge and Personal Behaviors 1–2 years of relevant experience in software engineering or AI/ML, including internships Good Python programming skills with Git and basic software testing (e.g. pytest), with the ability to provide evidence of this (e.g. GitHub portfolio, thesis or project work) Experience building at least one LLM application (e.g. a RAG prototype) and using LLM APIs (e.g. Azure OpenAI, Anthropic, AWS Bedrock) Basic knowledge of relational databases and SQL (e.g. PostgreSQL) Hands-on use of agentic AI tools for development and day-to-day work (e.g. GitHub Copilot, Cursor, Claude Code, Claude Cowork) Fluent English and good technical writing and documentation skills Good communication skills and ability to explain technical topics to non-technical colleagues Good analytical and problem-solving skills and strong attention to detail Eagerness to learn new tools and domains quickly and to act on feedback Good team-based interpersonal skills but also an ability to work independently and manage time effectively Desirable Skills and Experience Master’s degree in Artificial Intelligence, Machine Learning or Data Science Natural language processing and information extraction from unstructured documents (e.g. entity extraction, text classification) Advanced RAG techniques (embeddings, vector stores, chunking, hybrid search), agent orchestration frameworks (e.g. LangGraph) and Model Context Protocol (MCP) servers Building and consuming REST APIs (e.g. FastAPI), CI/CD, and integration and end-to-end testing SQL data modelling and query optimization Workflow automation (e.g. Python scripting, scheduled jobs, Power Automate) Exposure to Agile delivery (sprints, Jira) with merge-request-based code review Awareness of data protection requirements (e.g. GDPR) and responsible AI practice R and Shiny (R or Python) Docker and Linux Exposure to evidence synthesis or health economics and outcomes research (HEOR), such as systematic literature reviews or indirect treatment comparisons 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 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.