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Apply for this position and join us in building Europe’s next generation infrastructure.
Our values are rooted in responsibility, readiness, and long term thinking. We believe sovereignty must be designed into systems from the start. Readiness is achieved through capability, not procurement. Autonomy is infrastructure, not a feature. We build with the understanding that modern systems carry long term consequences. That is why we prioritise reliability over novelty, integration over isolation, and sustained capability over short term advantage.
Apply for this position
Position
Role Overview
Reports to: CTO
As our DevOps & Infrastructure Architect, you will own the full stack beneath the engineering organisation – from physical rack layouts and server specifications through to Kubernetes clusters, CI/CD pipelines, MLOps platforms, and the security controls that tie it all together. This is a hands-on architecture role: you will design the blueprint and build, deploy, and operate the running infrastructure. You serve embedded engineers, ML researchers, flight-software developers, and data analysts – teams whose workloads look nothing like a typical web-app shop. If you want to be the person who makes a defence-grade autonomous-systems company actually ship, this is the role.
Key Responsibilities
Experience & Skills
Required Qualifications & Experience
Apply for this position and join us in building Europe’s next generation infrastructure.
Our values are rooted in responsibility, readiness, and long term thinking. We believe sovereignty must be designed into systems from the start. Readiness is achieved through capability, not procurement. Autonomy is infrastructure, not a feature. We build with the understanding that modern systems carry long term consequences. That is why we prioritise reliability over novelty, integration over isolation, and sustained capability over short term advantage.
Apply for this position
Position
Role Overview
Reports to: CTO
As our DevOps & Infrastructure Architect, you will own the full stack beneath the engineering organisation – from physical rack layouts and server specifications through to Kubernetes clusters, CI/CD pipelines, MLOps platforms, and the security controls that tie it all together. This is a hands-on architecture role: you will design the blueprint and build, deploy, and operate the running infrastructure. You serve embedded engineers, ML researchers, flight-software developers, and data analysts – teams whose workloads look nothing like a typical web-app shop. If you want to be the person who makes a defence-grade autonomous-systems company actually ship, this is the role.
Key Responsibilities
- IT systems architecture – Design the full infrastructure stack: service topology, network segmentation, trust zones, rack layouts, power/cooling, and cabling. Maintain architecture docs, data-flow diagrams, and capacity plans the entire engineering org depends on.
- Hardware lifecycle management – Own assets from specification and procurement through deployment, maintenance, and decommissioning. Build hardware roadmaps tied to engineering growth forecasts so capacity is never the bottleneck.
- Server infrastructure – Size and deploy on-prem and hybrid compute environments serving concurrent workloads: GPU clusters for ML training and inference, tiered storage for telemetry and sensor datasets, analytics and BI tooling, development platforms, and local LLM deployment.
- Development platform administration – Deploy and operate self-hosted engineering tooling – primarily GitLab (SCM, CI/CD, registries, issue tracking) – plus artefact repositories, SAST scanners, and documentation platforms. Own high availability, backup/restore, and upgrade lifecycle for all dev tools.
- MLOps infrastructure – Build and maintain the ML lifecycle stack: experiment tracking, model registries, GPU-scheduled training orchestration, dataset versioning, and model serving pipelines. Ensure full reproducibility and auditability from data ingestion to edge deployment.
- Containerisation and orchestration – Design and operate the container platform: Docker builds pipelines, private registries, and Kubernetes clusters (RBAC, network policies, resource quotas, persistent storage, ingress). Manage deployments via Helm/Kustomize with GitOps-driven delivery.
- CI/CD pipeline architecture – Design scalable pipelines across heterogeneous codebases: embedded firmware with cross-compilation and HIL triggers, Python/C++ services, ML training jobs, and infrastructure-as-code. Implement secret management, signed artefacts, SBOM generation, runner fleet management, and parallelisation.
- Agile tooling and workflow support – Configure and maintain tooling for Agile workflows: issue tracking, sprint boards, branch-per-ticket and merge-request workflows with automated status transitions, CI-enforced Definition of Done, and engineering metrics dashboards.
- IT security architecture – Design and enforce security across the stack: network segmentation, firewall management, VPN/zero-trust access, IAM (LDAP/AD, SSO, MFA), PAM, endpoint security, vulnerability scanning, patch management, encrypted storage and transport, SIEM integration, and incident response. Support air-gapped environments where required.
- Monitoring, observability, and reliability – Implement infrastructure monitoring, log management, and alerting. Define SLAs/SLOs, build tested DR and business-continuity plans with clear RTO/RPO targets and failover procedures.
- Infrastructure as Code and automation – Manage all infrastructure through code: provisioning, config management, and automation scripting. Every infrastructure change goes through code review and CI validation before touching production.
Experience & Skills
Required Qualifications & Experience
- BS/MS in Computer Science, IT, Systems Engineering, or equivalent practical experience
- 7+ years in infrastructure, DevOps, or platform engineering; 3+ years in an architecture or tech-lead role
- Deep Linux admin (RHEL/Ubuntu/Debian): systemd, kernel tuning, LVM, production troubleshooting
- Physical and logical infrastructure design: compute/storage sizing, VLAN/subnet layout, firewall management, rack capacity planning
- Kubernetes in production (k8s, k3s, or OpenShift): cluster architecture, RBAC, NetworkPolicy, PV provisioning (Ceph, Longhorn, NFS), Ingress (NGINX, Traefik), resource quotas
- GitOps delivery with ArgoCD or Flux: Helm/Kustomize across dev/staging/prod, drift detection, and rollback
- CI/CD pipeline design at scale with GitLab CI (or Jenkins/GitHub Actions): pipeline topology, runner fleet management, Kaniko/DinD builds, artefact signing, SBOM generation, secret management (Vault, CI variables)
- Infrastructure-as-Code: Terraform or OpenTofu for provisioning, Ansible or Salt for config management, Bash/Python for automation
- Security architecture: LDAP/AD with SSO (SAML/OIDC, Keycloak), MFA, VPN/zero-trust (WireGuard, Tailscale, Cloudflare Access), TLS management, LUKS, vulnerability scanning (Trivy, Grype, OpenVAS), patch workflows
- Observability stack experience: metrics, log aggregation, alerting, and infrastructure monitoring
- Storage architecture: NAS/SAN (TrueNAS, NetApp), object storage (MinIO/S3-compatible), tiered hot/warm/cold strategies, backup/recovery (Restic, Borg, Velero) for multi-terabyte datasets
- Container expertise: multi-stage Docker builds, layer caching, private registry operation (Harbor, GitLab Registry), image scanning, runtime security
- Ability to translate engineering needs into infrastructure designs, trade-off analyses, and capacity roadmaps
- Clear technical documentation: architecture diagrams (draw.io, Mermaid), runbooks, operational procedures, post-incident reviews
- Hardware procurement and vendor management experience (servers, storage, networking, UPS)
- Comfortable in security-sensitive or defence-adjacent environments (access controls, audits, need-to-know policies)
- Collaborative mindset – infrastructure as a service to engineering teams
- English – Upper-Intermediate or above
- MLOps infrastructure: MLflow/Weights&Biases for experiment tracking, model registries, training orchestration (Kubeflow, Ray, SLURM), dataset versioning (DVC, LakeFS), model serving (Triton, Torch Serve), GPU operator and MIG partitioning
- Embedded and real-time systems CI: cross-compilation toolchains, hardware-in-the-loop (HIL) test integration, firmware signing and OTA update pipelines
- Edge deployment infrastructure: OTA update systems, lightweight container runtimes, remote management and telemetry collection from deployed UAVs
- Data engineering support: pipeline orchestration (Airflow, Prefect), data lake architecture, time-series and telemetry storage (InfluxDB, TimescaleDB), BI and analytics tooling (Grafana, Metabase)
- Regulated or certified environments: ISO 27001, SOC 2, DO-178C awareness; experience with audit trails, change management, and evidence collection
- Experience at a defence, aerospace, or deep-tech hardware company
- Familiarity with Luxembourg’s regulatory and data-sovereignty landscape
- Additional European language (French, German, or Luxembourgish)
Key Skills
Ranked by relevance
storage
cicd
kubernetes
embedded
gitlab
mlops
firewall
docker
devops
server
infrastructure as code
incident response
high availability
patch management
cloudflare
gitlab ci
terraform
kubeflow
ansible
grafana
linux
nginx
vault
siem
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- Posted
- May 12, 2026
- Type
- Full-time
- Level
- Not Applicable
- Location
- Luxembourg
- Company
- LUXUAV
Industries
Aviation
Aerospace Component Manufacturing
Categories
Information Technology
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