AI Engineer

AI Engineer

Envision Pharma Group

Cambridge, UK or Leiden, Netherlands

The opportunity

We are looking for a pragmatic AI Engineer who can bridge solid software engineering practices with the fast-evolving landscape of applied AI. You will help design, build, and evaluate AI systems that are reliable, measurable, and useful - not just demos.

You will work closely with data scientists, software engineers, and product managers to ship AI solutions that make real impact. You believe in evaluation before hype, automation where it adds leverage, and simple systems that perform well in production in the life sciences industry.

How will you make an impact at Envision Pharma Group?

Role responsibilities

• Develop and deploy AI-powered applications from prototype to production using modern LLM frameworks and APIs.
• Design evals and metrics that measure real-world performance (accuracy, latency, UX quality, safety).
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines integrating vector databases and LLMs.
• Implement data pipelines, retraining workflows, and monitoring tools that keep models current and performant.
• Develop and implement context engineering strategies to improve output quality and control hallucination risks.
• Collaborate with product, platform, and infrastructure teams to understand business needs and build systems that scale and fail gracefully.
• Apply agentic AI patterns (tool use, planning, reflection loops) pragmatically, choosing the right level of complexity for each use case.
• Champion good engineering practices: code reviews, testing, observability, CI/CD, reproducibility.
• Ensure AI solutions meet security, compliance, and explainability standards.

Do you have what we are looking for?

Skills & expertise

• 3+ years of experience in data science or software engineering, ideally with 2+ years focused on AI engineering.
• Proficiency in Python and experience with LLM APIs (OpenAI, Anthropic, or similar services).
• Experience with GenAI frameworks and libraries (LangChain, LlamaIndex, Haystack, or Hugging Face Transformers).
• Experience with vector databases (such as Pinecone, FAISS, Weaviate) and RAG pipeline implementation.
• Proven ability to evaluate AI systems through custom evals, benchmarking, or data curation.
• Developed and deployed AI-powered applications end-to-end, overseeing all phases from initial concept, prototyping & design through implementation, testing, and production launch.
• Familiarity with agentic AI concepts (tool-use, planning, multi-step reasoning), with a practical sense for when simpler systems suffice.
• Strong grounding in software engineering principles (version control, modular design, testing) and commitment to measurement-driven iteration.
• Excellent communication skills and the ability to explain complex AI solutions to non-technical stakeholders.
• Strong understanding of AI ethics, bias mitigation, and responsible AI practices.

Nice to have

• Experience with model fine-tuning, knowledge graphs, or multi-modal AI systems.
• Familiarity with AWS services for scalable GenAI deployment and MLOps practices.
• Demonstrated experience in direct client communication.