IT Infrastructure Engineer

REVEL captures the skill of experienced workers, turns it into robot intelligence, and deploys that capability where work is hard to staff. Neural Gambit captures the force, motion and intent behind expert work. RAI learns from that data. Genesis robots perform the resulting tasks on site.

The company was founded in 2025 and is building its founding team in the Czech Republic. Capture sessions, model training, the print fleet and robot test rigs all depend on local network, storage and compute.

You will design and operate the physical and computational infrastructure that the engineering, machine learning and content teams depend on: the network, the servers, the storage, and the compute those teams train and test on. You own everything from the cable in the wall to the job scheduler on the GPU nodes.

The work is hands-on and varied: racking and configuring hardware, designing network segmentation, diagnosing faults from firmware through to the kernel, and writing the provisioning and monitoring tooling that keeps it all visible. The systems are currently small enough for one person to administer directly, and are expected to grow quickly as capture volume and training load increase.

This role is paired with an IT Administrator who owns enterprise systems, identity and end-user support. You own the infrastructure layer; they own the accounts, devices and applications that sit on top of it. You will work closely together, and neither of you will be waiting on the other for the parts you own.

Design, build and operate the network: switching, routing, VLAN segmentation, firewalls, site-to-site and remote-access VPN, and wireless coverage across office, lab and workshop.

Run the network services the sites depend on: DHCP, internal DNS, NTP, RADIUS and certificate-based network authentication, and the ISP and failover links behind them.

Manage the physical estate: servers, GPU nodes, NAS and backup storage, racks, structured cabling, PDUs, UPS units, and the compute and peripherals attached to capture and test rigs. Maintain an inventory, a firmware baseline and a replacement schedule.

Build the computational infrastructure on top of that: shared high-throughput storage for capture and training data, job scheduling and GPU allocation, environment provisioning, and container and image registries, so that available CPU, GPU and disk capacity is used efficiently and fairly.

Own backup and recovery for research data and infrastructure state, including offsite copies, restore testing and a documented recovery plan for the training and capture pipelines.

Write internal tooling: monitoring, alerting, inventory, capacity and usage reporting, and simple web interfaces for administration.

Diagnose hardware and network faults, from cabling and optics through to driver, firmware and kernel-level problems, including GPU, NVMe and high-throughput networking issues.

Work with vendors, integrators and support organisations on warranties, RMAs, escalations and infrastructure procurement.

Support other teams with their infrastructure: advise on what they build themselves, resolve the issues they report, and write documentation so common problems can be handled without you.

Practical understanding of modern network infrastructure: L2/L3 switching, routing, VLANs, DHCP/DNS, firewalls, VPN and enterprise wireless.

Linux administration and bash. You can install, configure, automate and troubleshoot Linux systems from the command line, including storage, networking and boot-level problems.

Programming skills sufficient for internal tooling: scripts, small services and simple web interfaces for administration and monitoring. Python or an equivalent language.

Comfort working with physical hardware: racking, cabling, replacing components, and reading a vendor manual to the end.

Communication skills, and willingness to work on other people’s problems, including explaining causes and fixes to non-specialists.

Compute cluster administration (Slurm, Kubernetes or equivalent), including GPU scheduling and shared high-throughput storage.

Storage engineering: ZFS, Ceph, NFS or SMB at scale, tiering, and multi-terabyte dataset handling.

Configuration management and infrastructure-as-code (Ansible, Terraform, NixOS or similar).

Monitoring stacks such as Prometheus and Grafana.

Experience supporting a lab, workshop or manufacturing environment, including OT or machine networks kept separate from the office network.

Hybrid or cloud experience (AWS, GCP or Azure) for burst training capacity and offsite backup.

Full ownership of the infrastructure layer, including architectural decisions.

Hardware and model development in the same building, so the results of infrastructure work are visible directly.

[Compensation range, equity, benefits, relocation support to be filled in.]

Apply through the link on this posting. Include a short description of an infrastructure you built or took over: its scale, what you changed, and what problems you ran into.