AI infrastructure and enterprise IT services for Fortune 500
Cyber Space Technologies pairs deep enterprise IT services (cloud migration, SAP, Salesforce) with a serious AI infrastructure play. The tech stack—vLLM, TensorRT-LLM, Triton, Kubernetes, OpenShift AI—combined with active projects around high-performance inference and on-prem ML serving, reveals a shift toward LLM ops and GPU workload optimization. All 8 current open roles are senior-level engineering and data positions, suggesting they're scaling specialized talent for inference optimization and model serving rather than broad hiring.
Notable leadership hires: Salesforce Technical Lead
Cyber Space Technologies is a privately held IT solutions provider founded in 2001, headquartered in Edison, NJ, with 51–200 employees. The company serves Fortune 500 clients across cloud migration, managed IT services, SAP optimization, Salesforce implementation, and cybersecurity. Recent technical initiatives center on Kubernetes and OpenShift-based AI infrastructure, including on-premises ML serving platforms and GitHub enterprise migration. The service portfolio spans FinOps, data analytics, business intelligence, and application management.
Primary stack includes vLLM, TensorRT-LLM, Triton Inference Server, Kubernetes, OpenShift AI, AWS/Azure/GCP, Kafka, React, Angular, Node.js, Spring Boot, and SAP Commerce Cloud. Recent migrations target GitHub Enterprise and away from GitLab/Azure DevOps.
Active projects include on-premises Kubernetes/OpenShift AI platform deployment, high-performance LLM inference stack design, GitHub Enterprise migration, CI/CD modernization, and Salesforce solution architecture. Current focus areas are GPU utilization optimization and scaling LLM inference workloads.
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Cyber Space Technologies LLC's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.