Artificial Intelligence Engineer

Migx; Barcelona; Hybrid; EUR 90,000 - 130,000; Full time

Benefits offered by this job

Hybrid work model

25 holiday days per year

Career development opportunities

Fast-growing, international company

Job summary

Migx is seeking an Artificial Intelligence Engineer to join its Data and AI Engineering team. You’ll turn latest AI advances into production-ready tools, applications, and platforms, focusing on LLM-powered solutions for life sciences.

You’ll design scalable AI infrastructure, collaborate with Data and Backend Engineers, and contribute to CI/CD, testing, and observability. Fluency in English required; Catalan/Spanish is a plus.

Qualifications

• Hands-on experience deploying or building LLM-based systems.
• Proficiency in Python with FastAPI or similar frameworks.
• Experience with embeddings for text/document representation and semantic search.
• Familiarity with vector databases like FAISS, Weaviate or Pinecone.
• Understanding of AI infrastructure: versioning, tracking, and deployment with MLflow.
• Experience building production-grade APIs/services in an agile, collaborative environment.
• Awareness of AI ethics, responsible AI practices and explainability.

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 to support semantic search and information retrieval.
• Build scalable APIs and services using FastAPI or similar frameworks.
• Use MLflow to manage model experimentation, versioning, and deployment.
• Collaborate with Data Engineers 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.
• Support discussions on AI ethics, responsible usage, and explainability — especially for regulated use cases.
• Contribute to architectural decisions, product discussions, and agile ceremonies.

Skills

LLM experience

Python

FastAPI

Embeddings

Vector databases

MLflow

CI/CD

Agile

AI ethics

Tools

Docker

Kubernetes

LangChain

LLamaIndex

Azure

AWS

GCP

FAISS

Weaviate

Pinecone

MLOps

Job description

Position Name

Artificial Intelligence Engineer

About the profile

We’re looking for an 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.

Responsibilities

What You’ll Do

• 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 or similar frameworks.
• Use tools like MLflow to manage model experimentation, versioning, and deployment.
• Collaborate closely with Data Engineers 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.
• Support discussions on AI ethics, responsible usage, and explainability — especially for regulated use cases.
• Contribute to architectural decisions, product discussions, and agile ceremonies.

Requirements - Must have

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).

Requirements - Nice to have

Nice to Have

• Experience with Docker and Kubernetes for containerization and orchestration.
• Knowledge of prompt engineering, retrieval-augmented generation (RAG), or LangChain/LLamaIndex.
• Experience with cloud‑agnostic infrastructure or MLOps across Azure, AWS, or GCP.
• Background in regulated industries (life sciences), especially GxP environments.
• Familiarity with CI/CD pipelines and monitoring tools for AI workloads.
• Experience integrating LLMs into real-world applications such as chatbots, document classifiers, or summarizers.
• Spanish and/or Catalan language skills.

Languages

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

What we offer

What we offer

• Hybrid work model and flexible working schedule that would suit night owls and early birds.
• 25 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.