AI Platform Engineer - LLM Apps & Data Pipelines (Remote)

Speedcast; Madrid; Remoto; EUR 60.000 - 70.000; Tempo pieno

Descrizione del lavoro

Speedcast is seeking an Engineer (AI Platform & Data Engineering) to design and operate data pipelines and AI platform services from Spain-based remote work. You will work across data engineering, data science, and DevOps to deliver reliable AI-enabled solutions, focusing on ingestion, embeddings, vector stores, and APIs.

The role emphasizes production-ready data pipelines, security, governance, cost awareness, and cross-functional collaboration in a fast-growing, global team.

Competenze

• 3–5 years of experience in software engineering or data engineering.
• Proficient in Python and strong SQL skills.
• Experience developing and maintaining data pipelines in production.
• Experience integrating foundation model APIs (e.g., OpenAI, Anthropic) into applications.
• Hands-on AWS experience (Lambda, Step Functions, S3, Glue) and security best practices.
• Experience containerising applications with Docker.
• Experience building and operating APIs and backend services.
• Understanding of data quality, governance, and data engineering best practices.
• Experience with Git and Agile/Scrum environments.
• Strong analytical and communication skills.

Mansioni

• Design, build, and operate data pipelines powering AI applications.
• Productionize LLM-powered applications as reliable services with APIs and containers.
• Integrate AI workloads with lakehouse platforms (Kafka, batch sources, query layers).
• Build and maintain evaluation, logging, and feedback infrastructure for AI in production.
• Collaborate with data scientists, AI engineers, software engineers, and stakeholders.

Conoscenze

Python

SQL

Data pipelines

AWS

Docker

APIs

LLM integration

Strumenti

Kafka

Iceberg

S3

Descrizione del lavoro

Speedcast is seeking an Engineer (AI Platform & Data Engineering) to design and operate data pipelines and AI platform services from Spain-based remote work. You will work across data engineering, data science, and DevOps to deliver reliable AI-enabled solutions, focusing on ingestion, embeddings, vector stores, and APIs.

The role emphasizes production-ready data pipelines, security, governance, cost awareness, and cross-functional collaboration in a fast-growing, global team.