ABOUT US: 
Join our AI DevOps team, where we build and operate the infrastructure, frameworks, and tooling that enable AI engineers and data engineers to develop, deploy, and run AI applications at scale.
Our mission is to simplify the complexity of running AI workloads in production by providing a reliable and scalable platform built on Kubernetes and cloud infrastructure. We focus on automation, observability, developer-friendly frameworks, and cost-efficient infrastructure to enable teams to move quickly from experimentation to production.
You will play a key role in building and evolving the internal platforms that power our AI capabilities.
 
THE CHALLENGE: 
β’ Work closely with AI engineers and data engineers to design and maintain the infrastructure required to run AI and data workloads in production.
β’ Build and improve frameworks, tooling, and platform capabilities that simplify how teams develop, deploy, and operate AI applications.
β’ Develop and maintain Kubernetes-based platforms optimized for scalable and reliable AI workloads.
β’ Implement GitOps deployment workflows using ArgoCD and Helm to standardize and automate application deployments.
β’ Improve observability and monitoring across AI workloads using Grafana and Prometheus.
β’ Drive cost optimization initiatives, ensuring efficient usage of compute resources, storage, and cluster capacity.
β’ Automate infrastructure provisioning and platform configuration using Infrastructure as Code.
β’ Collaborate with engineering teams to gather feedback and continuously improve the AI platform and developer experience.
β’ Promote modern engineering practices including automation, reproducibility, observability, and secure infrastructure design.  
ABOUT YOU:
β’ You have experience working on production-grade systems and understand how applications are developed, deployed, and operated in modern environments.
β’ You enjoy improving developer workflows and building platforms that make it easier for teams to deploy, run, and scale their applications and data workloads.
β’ You have hands-on experience with Kubernetes and at least one cloud platform. Experience with AWS is considered a strong advantage.
β’ You are comfortable working with Infrastructure as Code tools such as Terraform or similar.
β’ You have experience with CI/CD or GitOps workflows, ideally with ArgoCD and Helm.
β’ You are familiar with monitoring and observability tools such as Grafana and Prometheus.
β’ You are comfortable writing automation or tooling in languages such as Python, Go, or Bash.
β’ You care about automation, reliability, and cost efficiency in cloud infrastructure.
β’ You enjoy collaborating with engineers across teams and contributing to modern engineering practices. NICE TO HAVE:
Experience with:
β’ Machine learning platforms or MLOps tooling
β’ GPU workloads and scheduling in Kubernetes
β’ Kubeflow, MLflow, or similar ML platforms
β’ Workflow orchestration tools (Airflow, Argo Workflows, Prefect)
β’ Data processing platforms such as Spark, Flink, or Kafka
β’ Model serving frameworks (KServe, Seldon)
β’ Cluster autoscaling and cost optimization strategies
β’ OpenTelemetry or distributed tracing 
 OUR OFFER:
β’ A collaborative environment with colleagues from all over the world (Engineering offices in Europe, Asia and US) including various social events and teambuilding. 
β’ Flexibility to manage your workday and tasks with autonomy. 
β’ A balance of structure and autonomy to tackle your daily tasks. 
β’ Vibrant and inclusive community, including Women in Tech and Pride groups which welcome all participants. 
β’ Global Employee Assistance Programme. 
β’ Calm and Reulay app (leading well-being apps designed to support focus, quality rest, mindfulness, and long-term mental resilience). 
β’ Online training videos. 
β’ Flexible working hours. While we appreciate the flexibility and benefits of working from home, we strongly believe that coming together in person fosters stronger connections, encourages collaboration, and drives innovationβboth as individuals and as a company. The energy, shared ideas, and team support we experience in the office strengthen the foundation of our success and culture. For this reason, we are an office-first business operating on a hybrid model, with team members working in the office three days a week to build relationships, exchange ideas, and grow together. 
 
OURβ―RECRUITMENTβ―PROCESS: 
β’ Initial Screening: A quick chat with our Talent Acquisition Partner to understand your background and expectations. 
β’ Technical Interview: Meet with the Technical team and later with the Hiring Manager.
β’ Onsite Interview: Meet with the local team and take a tour of our office for a final meet-and-greet. 
β’ Finals Steps: Receive feedback and, if successful, an offer!