I- Work from
- Albania, Andorra, Austria, Belarus, Belgium, Bosnia and Herzegovina, Bulgaria, Croatia, Cyprus, Czechia, Denmark, Estonia, Faroe Islands, Finland, France, Germany, Gibraltar, Greece, Guernsey, Holy See (Vatican City State), Hungary, Iceland, Ireland,
- Contract
- Full-time
- Experience
- Senior
- Posted
- 10 November 2026
- Apply by
- 9 January 2027
This specific role involves working with a leading European client to develop and maintain their sophisticated cloud platform. You will be responsible for defining the DevOps architecture and strategy for solutions built primarily on Microsoft Azure and Kubernetes. You will be a key player in ensuring that highly available, scalable, and secure cloud-native architectures are implemented, managing the full lifecycle from Infrastructure as Code (IaC) development through to CI/CD and observability.
Our Client is a long-established and highly-regarded Central and Eastern European technology provider specialising in designing, building, and operating advanced, mission-critical software solutions for large international organisations. With over 25 years of history and a team of 600+ top-tier software engineers across Europe, they are a certified partner for high-stakes industries including Aerospace & Defence, Automotive, Telecommunications, and Financial Services. They hold rigorous quality and security certifications such as NATO AQAP and TISAX.
This is a chance to apply your senior expertise to complex, enterprise-grade cloud environments.
Responsibilities
As a Senior DevOps Engineer specialising in AI and Data, you will be key to architecting and maintaining the infrastructure that supports large-scale AI/ML workloads. Your main responsibilities will be:
- Platform Deployment and Management: Design, build, and maintain scalable and secure cloud infrastructure for AI and Big Data solutions, ensuring high availability and performance in a production environment.
- AI/ML Infrastructure Automation: Implement end-to-end automation for the complete Machine Learning (ML) lifecycle, including infrastructure for model training, real-time inference, and data processing.
- Infrastructure as Code (IaC): Develop, manage, and optimise Infrastructure as Code (IaC) using tools like Terraform to provision and configure cloud resources consistently and efficiently.
- CI/CD Pipeline Development: Create, manage, and improve robust Continuous Integration and Continuous Delivery (CI/CD) pipelines to enable rapid and safe deployment of code, models, and infrastructure changes.
- Kubernetes for AI/Data: Manage and optimise Kubernetes clusters (e.g., AKS, EKS, or GKE) specifically tailored for running containerised data processing frameworks and GPU-enabled ML workloads at scale.
- Monitoring and Observability: Establish advanced monitoring, logging, and alerting systems to ensure the health, performance, and cost efficiency of the data and AI platforms.
- Security and Governance: Implement security measures, access controls, and compliance frameworks to ensure data privacy, model governance, and adherence to security best practices across all environments.
- Cross-Functional Collaboration: Work closely with Data Scientists, AI Engineers, and Software Development teams to translate complex AI requirements into robust, deployable infrastructure solutions.
Requirements
- Proven DevOps Experience: Strong professional background (5+ years) in a DevOps, SRE, or Cloud Engineering role, focusing on mission-critical production systems.
- Cloud Platform Expertise: Extensive, hands-on experience with at least one major cloud provider (AWS, Azure, or GCP), particularly related to infrastructure and networking.
- Kubernetes for Production: Expert-level knowledge of Kubernetes administration, operation, and optimisation for high-performance workloads, including scaling and resource management.
- Infrastructure as Code (IaC): Deep practical experience with Terraform for infrastructure provisioning and state management.
- CI/CD Systems: Proficiency in designing and managing automated CI/CD pipelines (e.g., Azure DevOps, GitHub Actions, or GitLab CI).
- Data/ML Tooling: Experience with tools and frameworks commonly used in the Data/AI domain, such as Apache Spark, Apache Airflow, Databricks, or specific AI/ML tooling infrastructure.
- Scripting: Solid proficiency in scripting languages like Python or Bash for automation, testing, and system integration.
- Monitoring: Experience implementing and working with observability stacks (e.g., Prometheus, Grafana, ELK stack, or cloud-native monitoring).
Our Client Offers
Our Client is committed to supporting your professional journey with a competitive package designed for growth, flexibility, and well-being.
- 100% Remote Work Option within Europe, providing ultimate work-life flexibility.
- Flexible Working Hours and a hybrid work model, supported by modern office hubs across Europe.
- Personalised Development Program and access to dedicated mentorship and coaching from domain experts to accelerate your career growth.
- Comprehensive Benefits Package, including additional health insurance and food vouchers.
- The chance to take full ownership and make a tangible impact on mission-critical, cloud-native solutions.
- A supportive, collaborative team culture with regular social events and team-building activities.
Do you need more information? Contact us directly
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