Infrastructure/Systems Engineer

• Infrastructure Engineer – Platform
• Company

Orcrist is building a next generation data intelligence platform using cutting-edge technologies.

We’re handling petabyte-scale data with sub-second queries.

Our product is a Kubernetes-based platform delivered as B2B Saa S or as a self-hosted on-prem solution, including air-gapped deployments.

We enable customers across defense, law enforcement, and enterprise to turn mission-critical data into actionable intelligence.

Our Platform team owns the infrastructure that powers every deployment, from the metal up.

Role

You'll own the layer everything else runs on: bare-metal servers, operating systems, data-center networking, and storage across on-prem and fully air-gapped sites — the physical and infrastructure foundation our platform and GPU fleets are built on.

You design, build, and operate server fleets with a strong automation and Dev Ops mindset, then partner with our SRE, MLOps, and ML teams to ensure everything running above the metal — including GPU inference — performs reliably at scale.

Some of this work is hands-on at customer sites, where you size, rack, and commission self-contained server environments with no internet uplink.

We weight depth in modern data-center infrastructure, networking, and automation more heavily than GPU-specific experience.

A strong infrastructure and network engineer with a genuine automation mindset — even without prior GPU exposure — is a better fit for this role than a candidate with GPU expertise whose networking background is rooted in legacy, corporate-style L2 designs.

What you'll do

• Design, size, provision, and operate bare-metal server fleets across on-prem and air-gapped environments (firmware/BIOS/UEFI, BMC via Redfish/IPMI, OS, RAID, kernel and storage tuning) using zero-touch provisioning (PXE/i PXE, MAAS/Metal3/Tinkerbell/Ironic) and automation (Ansible, Terraform, or equivalent — the tooling matters less than the automation mindset).
• Build and run modern data-center networking: L2/L3 design, IP Fabric, BGP and switching, and RDMA fabrics (Ro CE/Infini Band) sized to scale without ripping out the core.
• Engineer resilient, highly available storage (Ceph/Rook, NVMe) with capacity planning and encryption at rest.
• Operate confidently in air-gapped and on-prem environments: offline mirrors and registries, signed artifacts, firmware/driver lifecycle without internet access, and system hardening.
• Support MLOps and inference-serving fundamentals — GPU model serving (Triton/KServe/v LLM), GPU scheduling and sharing, and throughput/latency optimization — in partnership with our SRE and ML teams.
• Plan and run on-site build-outs: rack integration, power budgets, thermal/cooling and UPS sizing, commissioning, capacity planning, runbooks, and operator handover, with SWa P awareness for field sites.

About You

• 5+ years in bare-metal, data-center, or systems infrastructure engineering, with hands-on ownership of physical and compute infrastructure at scale.
• Strong bare-metal Linux (Ubuntu, RKE2, Talos, or similar): provisioning, firmware/BMC management, PXE/i PXE, kernel and storage tuning, systemd, RAID.
• Real experience with infrastructure automation (Ansible, Terraform, or equivalent), Git and CI/CD, and scripting in Python, Bash, or Go.
• Solid, current data-center networking fundamentals: L2/L3, IP Fabric, BGP, and switching — this is a hard requirement, not a nice-to-have.

RDMA (Ro CE/Infini Band) experience is a strong plus.

• Comfortable operating in air-gapped or on-prem environments and traveling to customer sites for builds and deployments.
• Practical hardware sizing literacy: power budgets, thermal/cooling, UPS sizing, and rack integration.
• Documentation-focused, methodical, and calm during hardware incidents. Eligible to work in Germany.
• Nice‑to‑haves
• German language (B1+); exposure to regulated or security-critical environments (e. g. BSI C5, ISO 27001, or defense-sector delivery) is a plus.
• NVIDIA GPU stack knowledge (drivers, CUDA, GPU Operator, MIG, DCGM) and cross-node GPU interconnect experience (NVLink, Infini Band, NCCL).
• Kubernetes bare-metal fundamentals — how cluster bring-up and GPU device plugins interact with the underlying hardware, not day-to-day cluster operation.
• Inference optimization (v LLM, Tensor RT-LLM, quantization) and familiarity with switch NOS (SONi C/Cumulus).
• Relevant certifications (NVIDIA, Red Hat, CKA/CKS) or field/forward-deployed engineering experience.

What We Offer

• Modern architecture & stack.
• Remote/Hybrid setup in Berlin with occasional team events in Berlin.
• Home office budget and great equipment.
• 30 days vacation.
• Direct impact on critical missions across private and public-sector customers.