AI Data Platform Solutions Architect

Location: Remote - California

Company

hirify.global develops enterprise and sovereign AI Data Platform solutions built on hirify.global storage, NVIDIA AI Enterprise, NVIDIA GPUs, and Supermicro reference hardware.

What you will do

• Serve as the primary NVIDIA AI Enterprise and vector database expert for HyperPOD customer environments.
• Lead complex end-to-end triage across GPUs, NVIDIA AI Enterprise services, vector databases, Kubernetes, containers, networking, and Infinia storage.
• Diagnose and resolve performance issues in RAG and agentic AI workflows, including retrieval latency, GPU utilization, and data access patterns.
• Define unified diagnostic bundles and collaborate on Prometheus, Grafana, ELK, and NetQ observability dashboards.
• Build hands-on labs, proofs of concept, known-good configurations, and reusable implementation and troubleshooting assets.
• Provide structured compatibility, upgrade, rollback, and observability feedback to Product Management, Engineering, NVIDIA, OEM, and vendor partners.

Requirements

• 5+ years of experience in Linux-based infrastructure roles such as SRE, MLOps, platform engineering, or L2/L3 production support; 8+ years of total technical experience preferred.
• Strong hands-on experience with Docker or containerd, Kubernetes, Helm, Operators, pods, DaemonSets, CSI, CNI, and ingress or load balancers.
• Production experience with NVIDIA GPUs, drivers, CUDA concepts, GPU performance triage, GPU Operator, and GPU cluster platforms such as DGX or HGX.
• Experience with high-performance storage, RDMA or InfiniBand and high-speed Ethernet networking, HPC/AI fabrics, and cloud-adjacent Kubernetes patterns.
• Experience operating vector databases such as Milvus, Qdrant, Pinecone, pgVector, or vector search in OpenSearch or Elasticsearch.
• Understanding of RAG, generative AI, embeddings, retrieval, reranking, prompt design, context management, NVIDIA AI Enterprise components, and MLOps or GenAI pipelines.

Nice to have

• Experience with scale-out storage and RDMA-accelerated HPC/AI clusters at scale.
• Hands-on experience with NVIDIA reference blueprints for Enterprise RAG, VSS, AIQ, or similar enterprise AI architectures.
• Familiarity with AI observability, responsible AI practices, guardrails, model drift, toxicity monitoring, and GDPR or HIPAA considerations.
• Experience tuning Prometheus, Grafana, Loki, ELK, or NetQ for AI workloads, service-level dashboards, and SLOs.

Culture & Benefits

• Work remotely from California as part of the Global Support Services product support organization.
• Collaborate with NVIDIA solutions architects, OEM architects, Professional Services, Support Innovation, Product Management, and Engineering.
• Operate across enterprise AI, storage, networking, observability, and customer support domains.