AI Engineer

Description

The team is expanding and is looking for an early-career Associate AI Engineer to help build AI tools for the Health Economics and HTA team.

Working alongside senior engineers, you will turn validated prototypes into production-grade AI tools, help build new prototypes with delivery teams, and keep existing tools running.

You get hands-on exposure to the full life cycle of AI solutions, from retrieval and extraction through drafting and quality control, applied to systematic literature reviews and evidence synthesis reports.

You will work in an Agile team spread across locations and functions and learn the health economics and HTA field on the job.

The company provides clinical research, commercial insights and healthcare intelligence to life sciences and healthcare organisations.

Responsibilities

• Rebuild validated prototypes as production agents on the enterprise AI development platform.
• Build reusable pipeline modules for retrieval, screening, data extraction, drafting and quality control that can be combined into agents for specific deliverables.
• Write tests and evaluation harnesses, and follow enterprise engineering standards.
• Build and refine AI workflows with delivery teams.
• Run pilots on live projects and measure the time they save.
• Handle routine runs and change requests for AI tools already in use.
• Package applications for deployment.
• Work in Agile sprints, managing the backlog and tickets in Jira.
• Raise a merge request for every change and address review feedback before anything ships.

Requirements

• A bachelor's degree in Computer Science, Computer Engineering, Electrical and Computer Engineering, Software Engineering, Informatics, Information Technology or Data Science is essential.
• A master's degree in Artificial Intelligence, Machine Learning or Data Science is preferred.
• 3-4 years of industry experience, including 2-3 years in AI/ML-related roles.
• Hands-on experience building LLM applications, and solid software engineering foundations including testing, version control and CI/CD.
• Ability to understand complex, document-heavy workflows and turn them into reliable, well-tested AI solutions.
• Advanced Python with strong software engineering practice: Git, CI/CD, unit, integration and end-to-end testing (e.g. pytest), and building and consuming REST APIs (e.g. FastAPI), with evidence of this from work or academic settings.
• Experience with RAG (embeddings, vector stores, chunking, hybrid search), tool calling, agent workflows and LLM APIs such as Azure OpenAI, Anthropic or AWS Bedrock.
• Experience with natural language processing and information extraction from unstructured documents, such as entity extraction and text classification, beyond prompting LLMs.
• Working knowledge of relational databases and SQL (e.g. PostgreSQL), including data modelling and query optimisation.
• Experience with workflow automation, such as Python scripting, scheduled jobs or Power Automate.
• Hands-on use of agentic AI tools in development and daily work, such as GitHub Copilot, Cursor, Claude Code or Claude Cowork.
• Exposure to Agile delivery (sprints, Jira) and merge-request-based code review.
• Fluent English and strong technical writing and documentation skills.
• Excellent communication skills, including explaining 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 teamwork skills, with the ability to work independently, take ownership of deliverables and manage time well.
• Desirable: experience in a regulated industry such as pharma, healthcare or finance, including handling confidential data, responsible AI practice and compliance such as GDPR.
• Desirable: computer vision for documents, including OCR, layout and table detection, and extracting data from figures.
• Desirable: experience with agent orchestration frameworks such as LangGraph and Model Context Protocol (MCP) servers.
• Desirable: LLM evaluation, monitoring and cost tracking, for example with LangSmith or Langfuse.
• Desirable: R and Shiny (in R or Python).
• Desirable: UI/UX design for internal tools and applications.
• Desirable: Docker and Linux.
• Desirable: exposure to evidence synthesis or health economics and outcomes research (HEOR), such as systematic literature reviews or indirect treatment comparisons.
• Desirable: exposure to the healthcare sector or the pharmaceutical market.

Conditions

Potential base pay is €31,200.00 to €46,800.00 annualized, depending on qualifications, location and whether the role is full or part-time.

Applications must be truthful and complete, as false statements or omissions can lead to disqualification or dismissal under applicable law.

Benefits

• Depending on the position, incentive plans, bonuses and other forms of compensation may be offered, along with health and welfare benefits.