Artificial Intelligence Engineer

Talcom; Madrid; Híbrido; EUR 60.000 - 80.000; Jornada completa

Descripción de la vacante

A health tech startup is seeking an AI Engineer (Python) to build and maintain AI solutions using machine learning for healthcare. This role offers a unique opportunity to innovate within a hybrid work environment in Madrid or Amsterdam, contributing to projects that improve healthcare for doctors and patients. The ideal candidate has strong Python skills, experience with FastAPI, and a background in data engineering.

Formación

• At least three years of software engineering experience.
• At least two years of experience with machine learning systems in production.
• Proven ownership and ability to complete complex projects independently.

Responsabilidades

• Build and maintain model pipelines that turn laboratory data into structured recommendations.
• Integrate and evaluate hosted and open source large language models.
• Create FastAPI services for inference and retrieval.
• Set up observability with OpenTelemetry and Langfuse.
• Design and maintain PostgreSQL data models.

Conocimientos

Strong Python skills

Experience with FastAPI

Data engineering and pipeline design

Familiarity with Docker

Familiarity with Kubernetes

Familiarity with Terraform

Knowledge of cloud providers (AWS, Azure, GCP)

Understanding of data privacy and European compliance

Educación

University Degree in Computer Science or comparable

Herramientas

PostgreSQL

Pandas

PySpark

DuckDB

Descripción del empleo

AI Engineer (Python) – Health Tech Startup in Madrid / Amsterdam

You will join Entera as the AI Engineer in a company that revolves entirely around artificial intelligence. This is an opportunity to help shape a platform where AI is not an add-on but the core of the product. You will design and run the intelligence that turns medical data into clinical insight. The work covers practical machine learning, backend development, and product design. You will collaborate closely with two experienced Engineers who act as consultants and ensure a strong technical foundation. It is a rare chance to build real‑world AI that directly improves healthcare for doctors and patients.

About Entera

Entera is a health tech startup founded by Michelle Martens and Ellen Pekelharing. Both founders share a deep interest in health, nutrition, and medical innovation, and started Entera to make advanced diagnostics more accessible and understandable. Michelle brings experience as a data scientist and product manager, while Ellen has a background in health and nutrition. Together they saw how difficult it is for doctors and patients to make sense of complex laboratory data.

Entera is building an AI platform that translates this complexity into clear and personal care reports. The system connects laboratories, doctors, and patients through a single environment. Laboratory data is automatically processed, interpreted, and converted into an actionable plan that can be shared with both doctor and patient. The reports are fully AI generated but always grounded in validated medical knowledge. This approach makes the process faster, more transparent, and easier to understand for everyone involved.

Entera has already signed its first partnership with a major laboratory in the Netherlands and is currently raising its first funding round. The company operates between Amsterdam and Madrid and is now building its first internal engineering team.

Responsibilities

• Build and maintain model pipelines that turn laboratory data into structured recommendations
• Integrate and evaluate hosted and open source large language models through SDKs or APIs
• Create FastAPI services for inference, retrieval, and evaluation with version control and automated tests
• Set up observability with OpenTelemetry and Langfuse to trace performance and feedback
• Design and maintain PostgreSQL data models with schema updates and safe migrations
• Build data processing pipelines using tools such as Pandas, PySpark, or DuckDB
• Apply agentic frameworks for reasoning and automation when relevant
• Deploy models in production with continuous integration and monitoring
• Work with the founders and the CTO as a Service engineers on roadmap and priorities

Requirements

• University Degree in Computer Science or comparable
• At least three years of software engineering experience
• At least two years of experience with machine learning systems in production
• Proven ownership and the ability to complete complex projects independently
• Strong Python skills and experience with FastAPI
• Experience with data engineering and pipeline design
• Familiarity with Docker, Kubernetes, Terraform, and one major cloud provider such as AWS, Azure, or GCP
• Understanding of data privacy and European compliance

Nice to Have

• Experience with medical or life science data
• Knowledge of retrieval augmented generation or vector databases
• Experience with European models such as Mistral or Gemma

Our Stack

Python, FastAPI, PostgreSQL, React, Docker, Kubernetes, Terraform, OpenTelemetry, Langfuse, EU based cloud

Work Setup

Hybrid I Amsterdam or Madrid in a WeWork office.