AI Platform Engineer

Role: AI Platform Engineer (Data, Infrastructure & Agentic Systems)

Location: Barcelona, Spain

6 months extendable contract

Mandatory: agentic AI

Key Responsibilities

• Engineer robust data and cloud foundations to support AI workloads and automation at scale across AWS environments.
• Design and implement agentic AI systems as part of a broader automation stack—developing self-orchestrating workflows, APIs, and reusable platform components.
• Build automation and observability solutions using Infrastructure-as-Code (Terraform/CDK) and modern monitoring frameworks.
• Integrate data pipelines with intelligent orchestration layers to enable autonomous experimentation and deployment.
• Collaborate across disciplines—partnering with data engineers, AI scientists, and platform specialists to embed AI capabilities into core operations.
• Champion responsible and scalable AI automation, ensuring compliance, reliability, and transparency by design.

Required Experience & Skills

• Strong software engineering background with Python, TypeScript, or similar languages.
• Proven experience building and automating cloud infrastructure using AWS (EC2, IAM, S3, Lambda, CloudWatch, etc.) and Infrastructure-as-Code tools (Terraform/CDK).
• Solid understanding of data engineering principles—pipeline design, data flow orchestration, and API integration.
• Experience with CI/CD pipelines and Git-based workflows.
• Demonstrated experience in use of AI tools (e.g., claude, Copilot, LangChain, agent frameworks) to enhance productivity.
• A self-driven, curious problem solver who experiments and iterates toward impactful solutions.

• Experience deploying or integrating agentic AI architectures, such as orchestration frameworks or autonomous agents.
• Knowledge of RAG pipelines, embeddings, and vector databases (e.g., Weaviate, Qdrant).
• Familiarity with Kubernetes/EKS and observability tools (New Relic, OpenTelemetry).
• Understanding of model hosting and optimization (vLLM, Triton, HuggingFace).
• Awareness of data governance and responsible AI practices in enterprise or regulated settings.