1,824,578open jobs
104,852companies
274,112added this week
Browse all
Location
In office

Confirmed on the employer's own hiring board on Oct 18, 2026. First seen by Alion on May 29, 2026. Radianarc scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Turn GPU infrastructure into real-world intelligence with sovereign AI, intelligent orchestration, GPU-as-a-Service, and cloud gaming solutions from Radian Arc.
Backed by BeAngels

About Radian Arc.

We’re specialists in outcome-optimized AI infrastructure - deploying, orchestrating and monetizing GPU compute where data, users and demand actually meet: inside telco networks, at the edge, and in core data centers. Not a generic AI platform. Not a consultancy. We’re the bridge between raw silicon and real-world results.

What impact you will have

Mission: Install, validate, operate, and maintain regional and core GPU cloud deployments across datacenter environments.

This role owns the practical deployment and operational readiness of the platform stack in the field. It bridges infrastructure engineering, datacenter operations, networking, host systems, storage, and platform operations. The engineer is responsible for taking a validated architecture and BOM and turning it into a working production environment, including physical deployment coordination, rack and cabling validation, switch and host bring-up, firmware and BIOS validation, operating-system installation, GPU and DPU validation, storage integration, platform stack installation, acceptance testing, and operational handover.

The role is intentionally hands-on and cross-domain. It is not a pure datacenter technician role, and it is not a pure platform engineering role. It is the person who can work in a datacenter, understand cabling and optics, debug host and network issues, validate GPU servers, support platform installation, and coordinate with engineering when problems arise.

The role is especially important as the platform evolves from regional deployments toward HGX-based GPU systems, east-west fabrics, and core AI infrastructure. This profile is focused on actual installation, commissioning, maintenance, and operational readiness.

What you’ll do

Datacenter deployment and commissioning

  • Coordinate physical deployment activities with datacenter providers, integrators, logistics teams, and internal engineering.
  • Validate rack layouts, elevations, power feeds, airflow assumptions, cable paths, and labeling before installation.
  • Support rack-and-stack activities for GPU nodes, CPU nodes, storage nodes, switches, firewalls, routers, serial/OOB equipment, PDUs, and supporting infrastructure.
  • Validate fibre and copper cabling against the deployment design, including OOB, north-south, east-west, storage, and management networks.
  • Validate optics, transceivers, link speeds, breakout cables, port mappings, and redundancy assumptions.
  • Maintain accurate as-built documentation, including rack elevations, cable maps, port maps, serial numbers, asset records, IP allocations, and change records.

Host and hardware bring-up

  • Bring up GPU servers, platform servers, storage nodes, and supporting infrastructure.
  • Validate BIOS, BMC, firmware, NIC, DPU, GPU, NVMe, RAID/HBA, and platform firmware versions.
  • Configure and validate BMC access using Redfish/IPMI and OOB management networks.
  • Validate GPU visibility, PCIe topology, NUMA layout, thermals, power behavior, and hardware health.
  • Run hardware acceptance tests, burn-in tests, GPU stress tests, network tests, and storage validation before handover.
  • Troubleshoot hardware issues across servers, GPUs, DPUs, NICs, optics, cables, disks, memory, firmware, and BIOS.

Network deployment support

  • Support deployment and validation of OOB, north-south, storage, and east-west networking.
  • Work with networking engineering to apply and validate switch configurations.
  • Validate BGP, ECMP, VLAN/VRF segmentation, EVPN/VXLAN where applicable, OVS/OVN integration, and routing reachability.
  • Validate VyOS routers, OOB firewalls, transit routers, Citrix NetScaler/WAF, and customer connectivity.
  • Support RoCE/RDMA fabric validation for distributed AI workloads where applicable.
  • Troubleshoot practical network issues such as link flaps, optics issues, incorrect polarity, MTU mismatches, route leaks, VLAN errors, packet loss, PFC/ECN issues, and fabric congestion.
  • Support integration with NVIDIA Cumulus / Spectrum-X environments, and assist with Cisco or SONiC-based alternatives if those become part of the roadmap.

Platform stack installation and validation

  • Support installation and validation of the platform stack across regional and core deployments.
  • Install and validate host operating systems, kernel versions, NVIDIA drivers, Mellanox/NVIDIA OFED or inbox drivers, CUDA compatibility, Docker/containerd, KVM/QEMU, and platform agents.
  • Support CloudStack-based deployments and Kubernetes/KubeVirt-based deployments.
  • Validate GPU passthrough, SR-IOV, BlueField NIC/DPU behavior, VM networking, and container networking.
  • Support Kubernetes node registration, GPU Operator validation, CSI validation, CNI validation, and node lifecycle workflows.
  • Support storage integration with StorPool, Weka, local NVMe, or other supported storage platforms.
  • Execute acceptance tests and produce deployment readiness reports.

Operational maintenance and Day-2 support

  • Perform controlled maintenance activities such as firmware upgrades, switch upgrades, host OS updates, GPU driver updates, BIOS changes, and hardware replacements.
  • Support incident response for infrastructure issues affecting GPU nodes, hosts, networking, storage, or platform components.
  • Perform root-cause analysis for deployment and operational failures.
  • Maintain runbooks for installation, validation, upgrade, rollback, troubleshooting, and handover.
  • Work with engineering to turn repeated operational issues into automation, better validation, or platform improvements.
  • Participate in on-call or escalation rotations for regional and core environments where appropriate.

Platform observability and validation

  • Ensure telemetry is correctly configured for hosts, GPUs, DPUs, switches, storage, OOB devices, and platform components.
  • Validate Zabbix, Prometheus, Grafana, Loki, DCGM/NVML, NVIDIA NetQ or equivalent telemetry sources.
  • Confirm that deployment health checks, hardware alerts, performance dashboards, and operational alarms work before production handover.
  • Support performance baseline testing for GPU, network, storage, and host layers.
  • Assist with NCP-related validation and benchmarking.

Cross-team coordination

  • Work closely with the Senior Director of Infrastructure Operations.
  • Work closely with Staff Network, Staff Storage, Sr Hardware/Infrastructure, Sr Platform, Sr Fleet Automation, Observability, Product Engineering, Sales Engineering, and Service Delivery roles.
  • Provide field feedback into reference architectures, BOMs, rack layouts, cabling standards, deployment playbooks, and validation procedures.
  • Coordinate with external vendors including datacenter providers, systems integrators, server vendors, storage vendors, NVIDIA, and networking vendors.
  • Act as the practical field escalation point when architecture, BOM, datacenter conditions, and platform implementation do not align.

Technical Stack

Hardware and datacenter

  • GPU servers: L40S, RTX 6000 Pro, H200, B200/B300-class systems, HGX systems, and future NVL72-style rack-scale systems.
  • CPU/platform servers.
  • Storage nodes and JBODs.
  • PDUs, BMCs, serial/OOB, firewalls, routers, switches.
  • Rack layouts, power feeds, airflow, cold/hot aisle containment, cabling, optics.
  • DTC/DLC cooling.

Host and systems

  • Ubuntu Linux.
  • Linux networking.
  • BIOS/BMC/firmware lifecycle.
  • Redfish, IPMI.
  • NVIDIA drivers, CUDA, DCGM/NVML.
  • Mellanox/NVIDIA NICs, BlueField DPUs.
  • KVM/QEMU, VFIO, PCI passthrough.
  • Docker/containerd.

Networking

  • NVIDIA Spectrum/Cumulus.
  • VyOS.
  • OVS/OVN.
  • BGP, ECMP, VLAN, VRF, EVPN/VXLAN.
  • RoCE/RDMA.
  • SR-IOV.
  • Citrix NetScaler / WAF.
  • OOB and break-glass access.

Platform

  • Kubernetes.
  • KubeVirt.
  • NVIDIA GPU Operator.
  • CSI/CNI integrations.
  • StorPool, Weka, local NVMe

Observability

  • Zabbix.
  • Prometheus.
  • Grafana.
  • Loki.
  • DCGM Exporter.
  • NVIDIA NetQ or equivalent.
  • Logs, metrics, hardware health, and deployment validation dashboards.

What you'll need

  • Strong hands-on experience deploying and maintaining datacenter infrastructure.
  • Experience with GPU, HPC, AI cloud, private cloud, or high-density compute environments, including both air-cooled and liquid-cooled (nice to have) deployments. 
  • Familiarity with NVL72-style rack-scale architecture, NVLink/NVSwitch domains, in-rack networking, high-density power delivery, and OEM/NVIDIA validation requirements.
  • Comfortable working across physical infrastructure, Linux hosts, networking, storage, and platform software.
  • Experience bringing up servers from bare metal through production readiness.
  • Experience with rack layouts, cabling, optics, transceivers, power, OOB management, and datacenter handover.
  • Strong Linux troubleshooting skills.
  • Practical networking knowledge across VLANs, VRFs, BGP, ECMP, OVS/OVN, and routing.
  • Experience with GPU servers, NVIDIA drivers, firmware, PCIe topology, and hardware validation..
  • Strong documentation discipline and ability to produce accurate as-built records and runbooks.
  • Ability to validate practical datacenter readiness for current and next-generation AI infrastructure, including power density, cooling model, rack depth/width, floor loading, containment, serviceability, and maintenance access.

Personal qualities:

  • Very hands-on and practical.
  • Comfortable working in datacenters and remotely with smart-hands teams.
  • Strong troubleshooting mindset across hardware, network, host, and platform layers.
  • High attention to detail around cabling, labeling, asset records, and validation.
  • Calm under pressure during deployment windows and customer-impacting incidents.
  • Able to distinguish between a temporary field workaround and a permanent engineering fix.
  • Good communicator who can explain field issues clearly to engineering and leadership.

What we offer

  • Attractive compensation package reflecting your expertise and experience.
  • A great work environment characterised by friendliness, international diversity, flexibility, and a hybrid-friendly approach.
  • You'll be part of a fast-growing scale-up with a mission to make a positive impact, offering an exciting career evolution.

Our job titles may span more than one job level. The actual base pay is dependent on a number of factors, such as transferable skills, work experience, business needs and market demands.

Our inclusive responsibility

Radian Arc is committed to creating a diverse and inclusive environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status, or any other protected category under applicable law.

Free account
Stop reading job ads. Get the ones that fit.
One free account turns this page into a shortlist built around your stack, your level and your pay.
Match on every job. Stack, seniority, pay and location, scored against your profile.
1,824,578 open roles. Read straight off company career pages, refreshed every day.
Unlimited applications. Every one you send is tracked in one place, on-site or on a company board.
3 tailored CVs a month. Rewritten for the exact job you are applying to. Included free.
Create a free account Continue with Google
Free forever. No card. Under a minute.

Your match

How well do you fit this role?
Two answers are enough for a real match. No account needed.
Check my fit
Answers stay in this browser until you create an account.

Recommended for you based on this role

AI/ML
Similar stack
Same company
In your city
≈ $144k – $295k per year (Estimated) • Equity • In office • 6+ years exp • Bachelor's Degree • Austin
Python
AI/ML
InfiniBand
DevOps
Linux
Apply
In office • Riyadh
Python
SQL
AI/ML
Computer Vision
NLP
TensorFlow
Pandas
NumPy
PyTorch
LLM
Text-to-Speech
Machine Learning
DevOps
Rest API
Git
Docker
Apply
AI Engineer 2 days ago
$121k – $266k per year • Hybrid • Full-Time • 5+ years exp • Bachelor's Degree • Washington
Python
AI/ML
LangGraph
LangChain
Function Calling
RAG
OpenAI
NIST AI RMF
Tool Use
Machine Learning
DevOps
Azure
CI/CD
Apply
AI Engineering Lead 2 days ago
$104k – $218k per year • Hybrid • Full-Time • Bachelor's Degree • Washington
Python
AI/ML
LangChain
Function Calling
AI Agents
RAG
OpenAI
NIST AI RMF
Tool Use
Machine Learning
DevOps
Azure
CI/CD
Apply
≈ $20k – $51k per year (Estimated) • In office • Full-Time • 7+ years exp • Bachelor's Degree • Kuala Lumpur
Python
Java
AI/ML
Reinforcement Learning
Scikit-learn
Computer Vision
TensorFlow
PyTorch
Amazon SageMaker
Machine Learning
DevOps
Azure
AWS
Apply
In office • 5+ years exp
Databases
MySQL
PostgreSQL
Redis
NATS
ClickHouse
RabbitMQ
Apache Kafka
DevOps
Terraform
Ansible
GCP
Zabbix
Istio
Linkerd
Prometheus
GitLab CI
Azure
CI/CD
AWS
Kubernetes
Grafana
Amazon EKS
Amazon EC2
Amazon S3
IAM
Amazon CloudWatch
Linux
DNS
Cybersecurity
PKI
Management
Confluence
Jira
Apply
$100k – $150k per year • Remote (United States) • 6+ years exp • Bachelor's Degree
Python
Java
DevOps
Splunk
Loki
New Relic
OpenTelemetry
Datadog
Prometheus
CI/CD
Grafana
Platform Engineering
Thanos
Mimir
eBPF
Cortex
Incident Management
Linux
Apply
≈ $13k – $25k per year (Estimated) • Hybrid • 1+ year exp • Moscow
DevOps
Ansible
Zabbix
Ubuntu
Linux
Windows
DNS
DHCP
VLAN
Cybersecurity
Active Directory
Apply
≈ $18k – $42k per year (Estimated) • Hybrid • 5+ years exp • Bachelor's Degree • Bengaluru
Rust
C++
AI/ML
CUDA Toolkit
AI Agents
OpenCL
LLM
CUDA
DevOps
Git
Management
Agile
Apply
≈ $85k – $173k per year (Estimated) • In office • Full-Time • Bachelor's Degree • Mississauga
Python
SQL
Databases
Snowflake
AI/ML
Spark
MLFlow
NLP
LLM
LLM Guardrails
Machine Learning
DevOps
Prometheus
Azure
AWS
Cortex
Analytics
Tableau
Power BI
Apply
≈ $83k – $186k per year (Estimated) • Remote (Europe) • Freelance • 7+ years exp
AI/ML
Claude Code
Management
Agile
Scrum
Apply
≈ $105k – $239k per year (Estimated) • Remote (Europe) • Full-Time
Python
Bash
AI/ML
TensorFlow
PyTorch
NCCL
DevOps
HPC
Linux
VLAN
BGP
OSPF
Web3
Layer 2
Apply
≈ $11k – $23k per year (Estimated) • Remote (Malaysia) • 3+ years exp • Kuala Lumpur
Python
Bash
AI/ML
Machine Learning
DevOps
Ansible
Zabbix
Prometheus
Kubernetes
Grafana
KVM
KubeVirt
SLI/SLO/SLA
HPC
Linux
TCP/IP
DNS
Apply
≈ $113k – $262k per year (Estimated) • Remote (Europe)
Python
Bash
AI/ML
Fine-tuning
LLM
KV Cache
DevOps
Kubernetes
Platform Engineering
Amazon S3
HPC
Linux
Apply
≈ $96k – $221k per year (Estimated) • In office • Full-Time • 7+ years exp
Python
AI/ML
AI Agents
LLM
InfiniBand
LLM Guardrails
Machine Learning
DevOps
Prometheus
Kubernetes
Cortex
IAM
Cybersecurity
Keycloak
Snort
HashiCorp Vault
Wazuh
TheHive
Authentik
Zero Trust
Least Privilege
HashiCorp Boundary
PKI
SIEM
Apply
See all jobs
This is one of many
1,824,578 more open roles from verified company boards, updated every day.