Artificial Intelligence Engineer

Quantiphi; Sevilla; Presencial; EUR 90.000 - 130.000; Jornada completa

Descripción de la vacante

Quantiphi Sevilla busca un Ingeniero de Inteligencia Artificial con 5+ años diseñando y desplegando plataformas de datos y soluciones agentic. Se requiere fluidez en inglés y español, y sólida experiencia en la pila GCP (AlloyDB, GCS, GKE, Gemini Enterprise, Vertex AI) junto con Python avanzado.

El rol implica crear y optimizar pipelines ML, automatizar DevOps/MLOps, y trabajar con iniciativas GenAI, LLM y RAG.

Formación

• 5+ años de experiencia diseñando y desplegando plataformas de datos y soluciones agentic.
• Experiencia en soluciones empresariales en la nube y gestión de proyectos para clientes.
• Certificación Google Cloud Professional ML Engineer (deseable).

Conocimientos

GCP Stack

AlloyDB

GCS

GKE

Gemini Enterprise

Agent Platform

BigQuery

Cloud Run

Vertex AI Pipelines

Python

Data structures

Algorithms

Software design

DevOps/MLOps

CI/CD

Kubeflow

Docker

Kubernetes

Linux

GenAI

LLM

RAG integration

Multi-cloud

Healthcare domain

Financial services domain

English/Spanish bilingual

Educación

Google Cloud Professional ML Engineer certification

Herramientas

Kubeflow

Docker

Kubernetes

Linux

Descripción del empleo

Artificial Intelligence Engineer Quantiphi Sevilla, metropolitana de sevilla (comarca); provincia de sevilla; andalucía, Spain

Descripción del trabajo

Role - AI Engineer

Location: Europe (Madrid, Spain preferred - travel to Spain customer site ideally once a month)

Language: Fluency in both English and Spanish required

Required Skills and Experience:

• 5+ years of experience designing, developing, and deploying high-performance data platforms and agentic solutions.
• Proven experience in designing cloud enterprise solutions and supporting customer projects through completion.
• Strong proficiency in the GCP stack: AlloyDB, GCS, GKE, Gemini Enterprise, and Agent Platform (formerly Vertex AI).
• Advanced Python coding skills, including data structures, algorithms, and software design.
• Experience in automating infrastructure provisioning, DevOps/MLOps, and CI/CD.
• Google Cloud Professional ML Engineer certification.

Technical Skills

• GCP Stack (Mandatory):
• AlloyDB, Google Cloud Storage (GCS), Google Kubernetes Engine (GKE)
• Gemini Enterprise, Agent Platform (formerly Vertex AI)
• BigQuery, Cloud Run, Vertex AI Pipelines
• Programming: Advanced Python skills including data structures, algorithms, and software design patterns.
• Agentic AI: Hands-on experience with AI Agents, Agent Development Kit (ADK), multi-agent frameworks, and RAG integration.
• MLOps/DevOps: Experience with Kubeflow, Docker, Kubernetes, and Linux environments.
• CI/CD: Proficiency in building and managing continuous integration and deployment pipelines.
• GenAI/LLM: Experience with LLMs, GenAI APIs, Model Garden, and GenAI Studio.

Good to Have

• Experience with AlloyDB and enterprise database solutions.
• Familiarity with PaLM embeddings and vector search technologies.
• Exposure to multi-cloud environments.
• Prior experience in healthcare, retail, or financial services domains.
• Additional GCP certifications (e.g., Professional Cloud Architect, Data Engineer).

Certification

• Google Cloud Professional Machine Learning Engineer certification (Good To have)