Telenet is a leading telco going all-in on cloud-first transformation, and we're looking for cloud-native engineers who share our passion for cloud infrastructure and Generative AI. In other words, people who build secure, scalable foundations that other teams reuse.
As part of the GenAI Cluster, you build and operate the cloud platform that powers Telenet’s Generative AI products. This includes everything from model hosting and inference to retrieval pipelines, automation and guardrails. All so that GenAI teams can move fast and ship responsibly.
Your mission as a Cloud Engineer GenAI
As a Cloud Engineer GenAI you design, build, automate and operate the cloud infrastructure behind our Generative AI workloads on AWS. This makes LLM and model serving reliable, scalable, secure and cost-efficient, and delivering reusable platform services to the product squads that build on top of them.
What you will do
- Build the GenAI platform. Design and maintain the cloud foundation for Generative AI on AWS (e.g. Amazon Bedrock, SageMaker, ECS and Fargate, fully described as infrastructure-as-code with Terraform.
- Run model serving & inference. Deploy, scale and operate LLM and model-serving / inference endpoints for latency, throughput, reliability and cost.
- Automate everything (CI/CD & LLMOps) . Build CI/CD and LLMOps pipelines for model and application deployment, evaluation and rollback, using GitLab CI and modern automation tooling.
- Enable retrieval & data plumbing . Stand up RAG and vector-database infrastructure, embedding pipelines and retrieval services that GenAI applications depend on.
- Secure the platform . Implement identity, network, secrets management (Vault), guardrails and compliance controls for GenAI workloads.
- Make it observable & affordable . Set up monitoring, logging, tracing and evaluation hooks, and drive performance and FinOps cost optimization.
- Champion cloud-native by design . Deliver consumable, well-documented platform services to GenAI and Predictive AI squads, promote cloud-native and automation-first ways of working, and help colleagues up- and cross-skill towards GenAI on the cloud.
Your profile as a Cloud Engineer GenAI
Must-haves
- Solid experience as a cloud, DevOps, platform or infrastructure engineer, ideally on AWS (certification is a plus).
- Understanding of Agentic AI: LLM tool calling, MCP and A2A
- Strong infrastructure-as-code skills (Terraform, CloudFormation) and hands-on experience with containers and Kubernetes.
- Experience building CI/CD pipelines (e.g. GitLab CI) and a strong automation mindset.
- Good scripting / programming ability, for example in Python.
- Solid grounding in networking, security, identity (IAM) and secrets management (e.g. Vault).
- A reliability- and cost-aware engineering attitude (SRE / FinOps thinking).
Nice-to-haves (GenAI focus)
- Familiarity with ML / GenAI workloads: model serving, and inference optimization.
- Familiarity Langchain, Langgraph and Langfuse
- Exposure to AWS Bedrock and/or SageMaker, vector databases and LLMOps / MLOps practices.
- Understanding of RAG architectures, embeddings and prompt/guardrail tooling.
Who you are
- Cloud-native by mindset, with genuine passion for Generative AI and emerging technology.
- A team player who thrives in agile squads and enjoys delivering services other teams build on.
- Fluent in English; knowledge of Dutch is a plus.
- Bachelor’s or Master’s degree in computer science or equivalent through experience.
Our offer to you
At Telenet, you get more than an attractive salary — we believe in results and ownership, and what you achieve truly matters.
On top of a thirteenth month and holiday pay, you can count on an extensive benefits package:
- Mobility budget: compose your own mobility plan, you can opt for a company car or alternative mobility solutions
- Meal vouchers and eco vouchers
- Mobile phone, mobile subscription, laptop, and employee discounts
- Collective bonus and individual bonus (aligned with your performance)
- Hospitalization insurance (including an ambulatory plan) and group insurance
- 20 days of paid leave and 12 compensatory days off
We invest in your growth via our internal learning platform, coaching and on-the-job training.
We work closely together, strong teams are built on frequent interaction. During your first six months we ask for at least three office days a week; after that, two.
What happens after you apply?
Apply if you see a match, we always get back to you. If your profile fits, we’ll reach out to schedule a first call and walk you through the next steps.
