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# AI Agent Developer

- **Company:** SIEMENS, S.A.
- **Location:** Barcelona, Spain (Remote available)
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Continuous Integration, Fault Tolerance, Python (Programming Language), Machine Learning, Software Engineering, AI Infrastructure, Data Logging, Delivery Pipeline, Large Language Models, Prompt Engineering, Backend, Information Technology, Api Design
- **Published:** August 4, 2026
- **Apply:** https://www.jobleads.com/es/job/e92e9a699e9f6d96289d6724083bc0e95

## About the Role

* 5+ years of software engineering experience, including 2+ years working with AI/ML solutions and deploying production systems.
 * Strong Python development skills with experience building APIs and backend services from development through deployment.
 * Knowledge of LLM integration techniques, including prompt engineering, RAG architectures, embeddings, and fine-tuning approaches.
 * Experience working with cloud platforms, preferably AWS, as well as CI/CD practices for deploying and monitoring AI workloads.
 * A practical, builder-oriented mindset with a passion for learning, creating real solutions, and continuously improving through hands-on experience.
 * A university degree in Computer Science, Engineering, or a related discipline, or equivalent professional experience.

## Description

* Design and develop agentic behaviours, including planning, tool-calling, and reasoning loops, while implementing verification mechanisms to reduce hallucinations and failure scenarios.
 * Build production-grade agent orchestration solutions that support complex handoffs, failure recovery, and graceful degradation in enterprise environments.
 * Implement auditable and self-monitoring agent workflows with robust logging, metrics, and human-in-the-loop escalation processes.
 * Contribute to shared AI infrastructure, including reusable templates, testing approaches, and deployment pipelines that accelerate development across the AI Factory.
 * Integrate LLMs and embeddings into applications and develop RAG pipelines that deliver accurate, domain-specific information for business users.


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