AI Engineer – Agentic Network Automation (Hybrid)

Vacaturebank; Amsterdam; Hybrid; EUR 58,000 - 87,000; Full time

Benefits offered by this job

13th-month salary

Development budget €1,500 yearly

Flexible leave days

Hybrid work: 2 days in office, 3 days@

Home office setup workshop

Travel reimbursement

Pension plan (23% total)

Bike lease option

Discount on products/services

Job summary

KPN is seeking an AI Engineer to design, build and maintain agentic AI solutions powering autonomous network optimization. You will collaborate with business stakeholders, domain experts, and engineering teams to create scalable AI platforms and ensure reliable real-time operation.

You will translate network objectives into data-driven models using reinforcement learning and stay updated on agentic AI innovations and telecom automation.

Qualifications

• Strong software engineering background with distributed systems in production.
• Hands-on experience deploying AI/ML in production environments.
• Familiarity with AI/ML frameworks and integrating models into software systems.
• Understanding of data pipelines, model serving, monitoring, and feedback loops.

Responsibilities

• Build, deploy, and maintain agentic AI systems for autonomous network optimization.
• Design system architectures, validate software quality, ensure production ownership.
• Develop scalable AI/ML pipelines emphasizing reliability and maintainability.
• Define monitoring, testing, and governance for production AI solutions.
• Collaborate with network experts, data engineers, and software teams to integrate solutions.

Skills

Python

Java

AI/ML in prod

AI frameworks

Distributed systems

Cloud-native

Reinforcement learning

Agentic AI

Job description

KPN is seeking an AI Engineer to design, build and maintain agentic AI solutions powering autonomous network optimization. You will collaborate with business stakeholders, domain experts, and engineering teams to create scalable AI platforms and ensure reliable real-time operation.

You will translate network objectives into data-driven models using reinforcement learning and stay updated on agentic AI innovations and telecom automation.