AI Engineer – Network at KPN designs, builds and maintains agentic AI solutions that power KPN’s move toward autonomous networks. You will create intelligent agents that observe, decide and act to optimize network performance in real time, collaborating with business stakeholders, domain experts and engineering teams to develop scalable AI platforms and production-ready solutions. Key responsibilities include building and maintaining agentic AI systems for autonomous network optimization (e.g., broadband disruption agent), ensuring production ownership, developing reliable AI/ML pipelines, and implementing monitoring, testing and governance to ensure robustness and compliance in production. You will translate network objectives into data-driven, self-adapting models using reinforcement learning and emerging AI tools, and stay up to date on agentic AI, reinforcement learning and telecom automation. You will integrate AI solutions into real-time network environments.

Qualifications: Strong software engineering background (distributed systems in production); experience with Python and/or Java and writing clean, maintainable code; hands-on production AI/ML experience (model deployment, monitoring, lifecycle management); experience with AI/ML frameworks and integrating models into larger software systems; understanding of end-to-end AI systems (data pipelines, model serving, monitoring, feedback loops); familiarity with cloud-native architectures (containers, CI/CD, scalable services); interest in reinforcement learning and agentic AI, with a drive to explore emerging framewor

AI Engineer – Network at KPN designs, builds and maintains agentic AI solutions that power KPN’s move toward autonomous networks. You will create intelligent agents that observe, decide and act to optimize network performance in real time, collaborating with business stakeholders, domain experts and engineering teams to develop scalable AI platforms and production-ready solutions. Key responsibilities include building and maintaining agentic AI systems for autonomous network optimization (e.g., broadband disruption agent), ensuring production ownership, developing reliable AI/ML pipelines, and implementing monitoring, testing and governance to ensure robustness and compliance in production. You will translate network objectives into data-driven, self-adapting models using reinforcement learning and emerging AI tools, and stay up to date on agentic AI, reinforcement learning and telecom automation. You will integrate AI solutions into real-time network environments.

Qualifications: Strong software engineering background (distributed systems in production); experience with Python and/or Java and writing clean, maintainable code; hands-on production AI/ML experience (model deployment, monitoring, lifecycle management); experience with AI/ML frameworks and integrating models into larger software systems; understanding of end-to-end AI systems (data pipelines, model serving, monitoring, feedback loops); familiarity with cloud-native architectures (containers, CI/CD, scalable services); interest in reinforcement learning and agentic AI, with a drive to explore emerging framewor