Artificial Intelligence Engineer

Responsibilities

• Design, build, and deploy
• LLM-powered applications
• and internal tools for use cases such as document understanding, process automation, and knowledge retrieval.
• Develop reusable
• AI infrastructure and platform components
• that support application teams (e.g., retrieval-augmented generation, prompt management, model orchestration).
• Work with
• embeddings, vector stores, and similarity search to enable contextual AI responses.
• Integrate with
• vector databases
• (e.g., FAISS, Weaviate, or Pinecone) to support semantic search and information retrieval.
• Build scalable APIs and services using
• FastAPI
• Use tools like
• MLflow
• to manage model experimentation, versioning, and deployment.
• Collaborate closely with
• Data Engineers
• Support discussions on

Preferred

• cloud-agnostic infrastructure
• or MLOps across Azure, AWS, or GCP.
• Background in regulated industries (life sciences), especially
• Experience integrating

AI Engineer

to join our

• Data and AI Engineering team. This role is ideal for those who are passionate about turning the latest AI advances - particularly
• LLMs (Large Language Models) into production-ready tools, applications, and platforms.
• You’ll work on the front lines of applied AI, helping to develop intelligent systems, scalable infrastructure, and internal platforms that power the next generation of life sciences solutions.
• Whether you're just getting started or bring years of hands-on experience, we welcome engineers who thrive in collaborative, exploratory, and engineering-focused environments.

What You’ll Do

• or similar frameworks.
• and

Backend Engineers

• to ensure smooth data access, secure service delivery, and continuous integration.
• Apply good engineering practices around testing, observability, and CI/CD for AI components.
• AI ethics, responsible usage, and explainability — especially for regulated use cases.
• Contribute to architectural decisions, product discussions, and agile ceremonies.

What We’re Looking For

• We believe diverse perspectives and backgrounds lead to better ideas. Even if you don’t meet every requirement, we’d still love to hear from you.
• Core Experience & Skills
• Hands-on experience working with or deploying

LLM-based systems

• (e.g., GPT, Claude, LLaMA, Mistral, etc.).
• Proficiency in

Python, with experience building services using

• FastAPI or similar frameworks.
• Working with embeddings for text or document representation and semantic search.

Familiarity with vector databases

(e.g., FAISS, Weaviate, Pinecone).

Understanding of

AI infrastructure: versioning, tracking, and deployment with tools like

MLflow

Exposure to building production-grade APIs, services, or workflows in an agile, collaborative environment.

Awareness of

AI ethics, responsible AI practices, and explainability concerns.

Team-first mindset and experience in agile environments

(Scrum or Kanban).

Experience with

Docker and

• Kubernetes for containerization and orchestration.
• Knowledge of prompt engineering, retrieval-augmented generation (RAG), or
• LangChain/LLamaIndex

Experience with

GxP environments.

Familiarity with

• CI/CD pipelines and monitoring tools for AI workloads.
• LLMs into real-world applications such as chatbots, document classifiers, or summarizers.
• Spanish and/or Catalan language skills (for Barcelona)

Languages

Professional working proficiency in English (our internal and client-facing working language).

What we offer

• Hybrid work model and flexible working schedule that would suit night owls and early birds.
• 24 holiday days per year.
• Opportunities for career development and to shape the company's future.
• An employee-centric culture directly inspired by employee feedback - your voice is heard, and your perspective encouraged.
• Different training programs to support your personal and professional development.
• Work in a fast growing, international company.
• Friendly atmosphere and supportive Management team.