Senior AI Platform Engineer – Production LLMs

Qualifyze; Barcelona; Hybrid; EUR 50,000 - 60,000; Full time

Benefits offered by this job

Hybrid working mode

Private health care

Meal allowances

Personal development budget

All-company European event

Job summary

Qualifyze is seeking an AI Engineer to join the Engineering team in Barcelona. You will take AI solutions from prototype to production, owning architecture, development, deployment, monitoring and cost optimization for LLM-based applications.

You will design and deploy production-ready LLMs, evaluate models, build cloud infrastructure, and maintain CI/CD pipelines. A strong Python background and experience with Docker/Kubernetes are required, with a preference for regulated industry exposure.

Qualifications

• Strong Python skills and backend API experience.
• Clear communication of technical decisions to teams and stakeholders.
• Structured, pragmatic problem solving with ownership.
• Experience with production ML/AI systems is highly desirable.

Responsibilities

• Design, develop and deploy production-ready LLM applications and RAG pipelines.
• Evaluate models/frameworks (OpenAI, Anthropic, Mistral) for various use cases.
• Build and manage cloud infrastructure for AI workloads (AWS, GCP, Azure).
• Maintain CI/CD pipelines and automated tests for AI services.
• Deploy and scale AI services using containers and orchestration tools.
• Monitor AI systems for latency, quality, drift and reliability.
• Optimize usage costs through model selection and batching.
• Investigate production AI issues and implement fixes.
• Stay updated on AI developments and toolchains.

Skills

Soft communication skills

Ownership & problem solving

Structured pragmatic approach

Team collaboration

Tools

Python

Docker

Kubernetes

Terraform

AWS

GCP

Job description

Qualifyze is seeking an AI Engineer to join the Engineering team in Barcelona. You will take AI solutions from prototype to production, owning architecture, development, deployment, monitoring and cost optimization for LLM-based applications.

You will design and deploy production-ready LLMs, evaluate models, build cloud infrastructure, and maintain CI/CD pipelines. A strong Python background and experience with Docker/Kubernetes are required, with a preference for regulated industry exposure.