Production AI Engineer: Trusted AI Workflows

Planet; Porto; Híbrido; EUR 60 000 - 90 000; Tempo integral

Resumo da oferta

Planet is seeking a hands-on AI/ML production engineer to own design, delivery, and continuous improvement of AI workflows automating internal processes across HR, Finance, Operations, and CRM. You will build agents, prompts, and retrieval pipelines that business users can trust and iterate them using real-world feedback.

The role emphasizes production-quality decisions, observability, and governance, with collaboration across Data Engineering and enterprise platforms.

Qualificações

• Strong software engineering background with production systems experience.
• Hands-on experience with AI/ML systems (LLMs, classifiers, decision models).
• Experience integrating APIs and distributed systems.
• Experience designing prompts, retrieval pipelines, or ML inference workflows.
• Solid understanding of model evaluation, monitoring, and feedback loops.

Responsabilidades

• Design and build production-grade AI workflows across internal systems (HR, Finance, Operations, CRM).
• Implement orchestration logic—triggers, retries, fallbacks, and human-in-the-loop patterns.
• Develop and maintain the AI agents, prompts, retrieval pipelines, and decision logic.
• Own model behaviour in production: accuracy, failure modes, edge-case handling.
• Iterate on model performance using evaluation frameworks and real-world usage data.
• Take accountability for decision quality and outcomes with defined success metrics.
• Collaborate with Data Engineering on data pipelines, security and governance.

Conhecimentos

Software engineering

Python

AI/ML systems

APIs

Distributed systems

Prompts design

Retrieval pipelines

Model evaluation

Production systems

Ferramentas

Temporal

Airflow

Step Functions

Descrição da oferta de emprego

Planet is seeking a hands-on AI/ML production engineer to own design, delivery, and continuous improvement of AI workflows automating internal processes across HR, Finance, Operations, and CRM. You will build agents, prompts, and retrieval pipelines that business users can trust and iterate them using real-world feedback.

The role emphasizes production-quality decisions, observability, and governance, with collaboration across Data Engineering and enterprise platforms.