AI Engineer

Overview of the Role

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

Hands-on experience building LLM applications and strong software engineering foundations, including testing, version control and CI/CD, are essential.

The role requires the ability to understand complex, document-heavy workflows and translate them into reliable, well-tested AI solutions.

Exposure to the healthcare sector or the pharmaceutical market is desirable.

Responsibilities

Production Solutions

Rebuild validated prototypes as production agents on our enterprise AI development platform.

Build reusable pipeline modules (retrieval, screening, data extraction, drafting and quality control) that can be combined into deliverable-specific agents.

Write tests and evaluation harnesses and follow enterprise engineering standards.

Prototyping

Build and refine AI workflows together with delivery teams.

Run pilots on live projects and measure the time saved.

Support

Handle routine runs and change requests for AI tools already in use.

Package applications for deployment.

Ways of Working

Work in Agile sprints, managing the backlog and 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.

Master's degree in Artificial Intelligence, Machine Learning or Data Science is preferred.

Essential Skills, Knowledge and Personal Behaviors

3-4 years of industry experience, including 2-3 years in AI/ML-related roles.

Advanced Python programming with strong software engineering practice (Git, CI/CD, unit, integration and end-to-end testing, e.g. pytest), including building and consuming REST APIs (e.g. FastAPI), with the ability to provide evidence of this applied in a business or academic setting.

Hands-on experience building LLM applications: RAG (embeddings, vector stores, chunking, hybrid search) Tool calling and agent workflows Using LLM APIs (e.g. Azure OpenAI, Anthropic, AWS Bedrock)

Experience in natural language processing and information extraction from unstructured documents (e.g. entity extraction, text classification) beyond LLM prompting.

Working with relational databases and SQL (e.g. PostgreSQL), including data modelling and query optimization.

Experience with workflow automation (e.g. Python scripting, scheduled jobs, Power Automate).

Hands-on use of agentic AI tools for development and day-to-day work (e.g. GitHub Copilot, Cursor, Claude Code, Claude Cowork).

Exposure to Agile delivery (sprints, Jira) with merge-request-based code review.

Fluent English and strong technical writing and documentation skills.

Excellent communication skills and ability to convey technical topics to business stakeholders and subject-matter experts.

Excellent analytical and problem-solving skills, strong attention to detail and the ability to learn new tools and domains quickly.

Good team-based interpersonal skills but also an ability to work independently, take ownership of deliverables and manage time effectively.

Desirable Skills and Experience

Experience in a regulated industry (e.g. pharma, healthcare, finance), including handling confidential data, responsible AI practice and compliance requirements such as GDPR.

Computer vision for documents (OCR, layout and table detection, extracting data from figures).

Experience with agent orchestration frameworks (e.g. LangGraph) and Model Context Protocol (MCP) servers.

LLM evaluation, monitoring and cost tracking (e.g. LangSmith, Langfuse).

R.

Shiny (R or Python).

UI/UX design for internal tools and applications.

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.