Platform Engineer

• Operate, maintain, and sustainably scale Linux systems
• Automate recurring tasks using modern configuration management tools
• Ensure the stable operation of publicly accessible web applications and platforms
• Maintain monitoring with Grafana, Loki, or Zabbix
• Support automated CI/CD pipelines and drive continuous integration forward
• Analyze challenges and support the team with incident response

In-House DevOps / Platform Engineer

• Operate the Linux server environment, including on-premises clusters (Proxmox, ZFS) and AWS
• Operate and harden networks and security infrastructure, including firewalls, VPNs, access control, certificates, and system hardening
• Manage network connectivity with the largest partner
• Automate infrastructure with Ansible, including version control, reproducibility, and documentation
• Manage the container platform (Docker, Nomad, Traefik)
• Manage CI/CD pipelines with GitHub Actions
• Administer MySQL in production, including backups, performance, and recovery
• Expand monitoring, logging, and alerting with Grafana and New Relic
• Conduct incident analyses through to root cause
• Act as a sparring partner for Engineering, Data, and Product
• Explain technical architecture decisions

Senior Systems Engineer – Platform & Security

• Plan, coordinate, and implement IT projects
• Work closely with the Development, Quality Management, Cybersecurity, Service, and Support teams
• Design, configure, install, and maintain hardware and software in the company’s geographically redundant data centers based on automation concepts, increasingly incorporating cloud solutions
• Install, configure, and maintain servers in virtualized environments, as well as Linux-based services and applications
• Perform updates, patches, and release upgrades
• Implement hardening measures and countermeasures against common attack patterns
• Ensure device compliance
• Manage tickets and provide second-level support for laboratory inquiries

Linux Platform Engineer

• Plan, build, and operate highly available AI/ML platforms and services based on Kubernetes across on-premises, hybrid, and cloud environments
• Design and implement scalable GPU infrastructures in Kubernetes clusters, including GPU scheduling and sharing
• Build and operate model-serving and inference services for traditional ML models and Large Language Models
• Develop and operate MLOps/LLMOps workflows for production-grade GenAI services
• Implement guardrails, policies, evaluations, regression testing, and cost and quality monitoring
• Provide fine-tuning and re-training workflows
• Monitor, troubleshoot, and performance-tune AI platforms
• Advise customers on best practices, AI governance, data security, and data privacy
• Collaborate with data science, data platform, and development teams to integrate AI solutions
• In the Senior role: take ownership of architecture, make key technology decisions, provide technical leadership in customer projects, and mentor colleagues

Senior AI Platform Engineer

• Provision, configure, secure, and operate Kubernetes infrastructures in on-premises environments or customers’ dedicated cloud environments
• Manage storage, networking, and monitoring components
• Install, deploy, and regularly update products and services on Kubernetes platforms
• Ensure the reliable operation of products and services
• Support the support team with complex technical issues
• Analyze incidents affecting platform and product operations
• Implement sustainable, long-term solutions to resolve issues
• Comply with ISMS processes, for example in accordance with ISO 27001/C5
• Contribute to the verifiability of operational security

Platform Operations Engineer, E-Health

• Build and operate the internal developer platform and its tooling and infrastructure
• Enable product teams to set up and run their own services independently
• Drive cloud migration by moving and consolidating services into a modern cloud-native setup
• Design system and infrastructure architecture
• Communicate architecture clearly through diagrams and other documentation
• Work directly with product engineers to resolve infrastructure problems and unblock delivery
• Deliver with coding agents and improve how the wider team uses them

Senior Infrastructure, DX Engineer – Platform

• Own platform foundations end-to-end, from AWS architecture and infrastructure as code to CI/CD, observability, and incident readiness
• Build and evolve secure, scalable AWS infrastructure covering networking, compute, storage, and IAM, optimized for reliability and cost
• Design and maintain fast, repeatable, developer-friendly GitHub CI/CD pipelines with clear feedback loops, safe deployments, and strong defaults
• Define and operate infrastructure using Terraform with clean modules, sensible standards, and automated validation
• Improve developer experience through golden paths, templates, self-service environments, paved deployment roads, and internal tooling
• Drive availability, scalability, and resilience through deployment strategies, rollbacks, capacity planning, disaster recovery thinking, and performance tuning
• Implement security-by-default practices including least-privilege IAM, secrets management, secure supply chain, and enabling guardrails
• Establish and refine observability and reliability practices including SLOs, SLIs, monitoring, alerting, postmortems, and runbooks
• Partner with product engineering to reduce operational load and maintain delivery velocity as Zalion grows

• Take technical ownership of MAIA’s production infrastructure
• Operate and evolve self-administered Linux systems across virtual machines and dedicated servers
• Manage containers, networks, reverse proxies, and API gateways
• Improve Infrastructure as Code, GitHub Actions workflows, deployment processes, automated checks, versioning, and rollback capabilities
• Make deployments safe, repeatable, and easy for engineers to use
• Operate and improve PostgreSQL in production, including performance analysis, connection pooling, capacity planning, backups, and tested restore procedures
• Develop the self-hosted observability stack connecting metrics, logs, traces, and actionable alerts
• Strengthen infrastructure security through IAM, least privilege, secrets management, TLS, vulnerability scanning, and patch management
• Implement technical controls for ISO 27001 with continuously generated, understandable, and auditable evidence
• Shape AI infrastructure by integrating and evaluating model and inference providers
• Evaluate providers based on reliability, latency, throughput, cost, and operational effort
• Explore self-hosted LLM inference, potentially including GPU infrastructure and vLLM
• Improve incident response and operational resilience through root-cause investigation, runbooks, documentation, and lasting improvements
• Improve internal developer experience by reducing manual work and creating clear interfaces and workflows
• Make infrastructure and inference costs transparent and inform build, buy, and hosting decisions
• Assess the existing platform, identify risks, explain options, and take improvements through to reliable production operation
• Collaborate with software engineers, the CTO, company leadership, and distributed team members
• Work as a hands-on senior individual contributor without people management

Senior DevOps / Platform Engineer, AI Infrastructure

• Take technical ownership of infrastructure and operations as the first dedicated Senior DevOps / Platform Engineer
• Evolve the existing platform architecture, automation, and operational standards
• Operate self-administered Linux systems on European VMs and dedicated servers
• Integrate AWS, Azure, and GCP services
• Operate and further develop Docker Compose, networks, reverse proxies, and API gateways
• Develop Infrastructure as Code, CI/CD, and deployment workflows
• Implement automated checks, traceable configurations, and tested rollback procedures
• Take responsibility for PostgreSQL in production
• Analyze and optimize performance, connection pooling, and capacity
• Set up and validate reliable backup and restore procedures
• Further develop the self-hosted observability stack with metrics, logs, traces, and actionable alerting
• Implement least privilege, secrets management, vulnerability scanning, and patch management
• Implement technical measures and automated evidence collection for the ISO 27001 initiative
• Evaluate inference providers and operating models based on latency, throughput, cost, and reliability
• Build and operate an in-house LLM serving environment on GPU infrastructure over time
• Automate recurring operational tasks and document operating procedures
• Systematically investigate incidents and implement lasting improvements
• Collaborate with Engineering and the executive team without people-management responsibilities