Job Specifications
Senior AI Engineer
Work Model: 1 day a week on site in Ghent
Contract Length: 12-24months to perm
Workload: 40 hours a week
Start Date : ASAP
About the Role
We are looking for a Senior AI Engineer to develop production-ready AI systems that power software products in the biopharma industry. This is a hands-on role where you will design, implement, and maintain AI-driven features leveraging large language models, agent orchestration frameworks, and retrieval-augmented generation (RAG) architectures.
As part of an agile engineering team, you will write code daily - building sophisticated agentic workflows and ensuring they perform reliably in production. You’ll take ownership of the entire AI system lifecycle, from design and implementation to validation and deployment, translating complex domain requirements into robust technical solutions.
You’ll primarily work across LLMs, agent orchestration, and RAG implementation - leveraging providers like OpenAI, frameworks such as LangGraph, and retrieval stacks (e.g., Elasticsearch with ClickHouse). You will containerize with Docker and deploy to on-premise or cloud systems (Azure/AWS).
The role follows a hybrid work model with one day per week on-site and the remainder flexible.
Key Responsibilities
· Design & implement deterministic, stateful agent workflows with RAG (multi-step reasoning, tool-use, retries/fallbacks, human-in-the-loop).
· Engineer retrieval pipelines (chunking, embeddings, re-ranking, hybrid search) and query rewriting to boost performance.
· Drive LLMOps: tracing, evaluation, observability, CI/CD.
· Lead quality assurance: unit/integration/e2e tests for agent flows.
· Document architectures and patterns; mentor peers; stay current with LLM providers and agent methodologiess.
Requirements
· Master’s or PhD in Computer Science, Software Engineering, Data Science, or a related field.
· 5+ years of experience in software or AI engineering, including at least 1 year building LLM-based agents in production.
· Strong Python coding skills and a hands-on approach to building reliable, scalable solutions.
· Experience with semantic search or vector databases for retrieval-augmented generation workflows.
· Ability to understand, write, and troubleshoot SQL queries against relational databases as part of agent workflows.
· Experience containerizing and deploying agents.
· Nice-to-have: ELT for RAG, observability frameworks for RAG, life-sciences domain exposure (e.g., SAR data), ML fundamentals, API development.
Nice to Haves
· Experience with ML fundamentals, model training/evaluation, and MLOps
· Background in biotech, biopharma, or life sciences, especially experience with structure-activity relationship (SAR) data
What do we offer?
· A challenging job environment with advancement opportunities
· Possibility to work from home in an international (global) setting – hybrid remote setting with possibility to connect with colleagues in Ghent on-site
· A dynamic company with an open culture, easy communication and ambitious vision
· A rich & global team with a mix of backgrounds, experiences and expertise
· Independence and flexibility
About the Company
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