Ai Engineer

The life sciences industry plays a significant role in advancing healthcare and improving the quality of life - in many cases, saving millions of lives globally. At BASE life science, this is the motivation for everything we do, aimed at pushing boundaries, seeking excellence, and making a lasting difference through consulting expertise and data-driven solutions.

**Who is BASE life science?**:
Founded in 2007, BASE life science is a business and technology consulting enterprise working exclusively in the life sciences industry.

From our headquarters in Denmark and offices in France, Germany, Italy, Spain, Switzerland, the United Kingdom, and the United States of America, we serve customers across the globe. With a deep understanding of the life sciences industry, we work hand in hand with customers to identify, develop, and implement strategic initiatives that drive growth, efficiency, and overall success through tailored solutions.

Our partnership with industry-leading solution providers, including Veeva, Salesforce, IQVIA, Benchling, and MediSpend ensures that our clients harness the full potential of the most innovative solutions on the market.

**About the role**:
We are looking for AI Engineers excited about the power of large language models (LLMs) to help us transform the complex processes of the life science industry. You will work at the intersection of AI and life sciences to build smart, secure tools that streamline how our customers create, review, and manage critical documents—from clinical study protocols and reports to regulatory submissions and promotional materials.

You will be working with enterprise-grade LLMs (like OpenAI, Anthropic, and Cohere) through cloud platforms like AWS, Azure, or Google Cloud. The focus is on applied AI — no need to build custom models from scratch. Instead, you will leverage and tune state-of-the-art language generation capabilities to solve real-world problems for medical writers, regulatory teams, and commercial functions.

We are looking to hire multiple people, and the seniority of the position will be based on your skill-set and professional experience.

As an AI Engineer your responsibilities include:

- Design and deploy AI-powered tools that help teams draft, review, and analyse documents such as:

- Clinical study protocols and clinical study reports (CSPs & CSRs) - and all of their associated documents.
- Health Authority Q&A packages.
- Medical, legal, and regulatory (MLR) content review.
- Use enterprise LLMs to build features like summarization, document comparison, question answering, content classification, and redaction.
- Develop pipelines using retrieval-augmented generation (RAG) and integrate vector search to enhance context and relevance.
- Ensure solutions are secure, auditable, and scalable in regulated cloud environments (e.g., AWS, Azure, GCP).
- Work closely with regulatory, clinical, and commercial teams to understand their workflows and co-create AI tools that actually help.

We offer this position in Barcelona or Madrid, Spain.

**What makes you the best person for this job?**:

- You enjoy building reliable AI tools that make complex work simpler—and more human.
- You’re curious about how the life sciences industry works and want to make a tangible impact.
- You’re excited about working in a highly cross-functional environment, collaborating with both technical and non-technical experts.
- You learn fast, care about product/project delivery and quality, and thrive in a fast-evolving space.
- You have strong communication skills in English.

On top of this, you have the following core competences:

- Strong Python skills with experience in LLM orchestration libraries (e.g., LangChain, LlamaIndex, Haystack, Semantic Kernel), chain-of-thought, and structured reasoning approaches.
- Hands-on experience with enterprise LLMs - their APIs, performance challenges, and how to mitigate those (OpenAI, Anthropic, Cohere, etc.)
- Demonstrated production experience with APIs’ conventions and integration into pipelines, e.g. RESTful API, FastAPI, or similar.
- Experience integrating multiple approaches for extracting highest-quality output from LLMs, e.g. prompt engineering, agentic
- and graph-RAG, in-context learning (ICL), or NLP- or ontology-powered layering.
- Proficiency with document processing pipelines (text extraction, chunking, embedding).
- Strong foundation in data science fundamentals, including data analysis, statistical methods, and experience working with structured and unstructured data (preferably in healthcare or pharmaceutical contexts).
- Experience with cloud services (AWS, GCP, or Azure).

It will be a plus if you have these additional capabilities:

- Experience with semantic computing and document structuring, e.g. using MarkDown, LaTeX, or other taxonomic approaches.
- Understanding of the pharmaceutical clinical and regulatory documents & workflows.
- Proficiency with vector databases (Pinecone, Weaviate, Chroma, e