AI Enablement Engineer – NVIDIA AI Enterprise & Kubernetes

AI Enablement Engineer – Private AI & NVIDIA AI Enterprise on Kubernetes

Location: Stockholm, Sweden (Hybrid – 2 days per week in office)

Contract: 12+ months

Ampstek is hiring for a large enterprise client building a private AI platform on VMware and NVIDIA GPUs. You will deploy, configure and validate the AI software stack that internal teams use to run LLM workloads on Kubernetes.

What you will do

• Deploy and configure VMware Private AI Foundation with NVIDIA and NVIDIA AI Enterprise components, including NIM microservices and NeMo Guardrails

• Configure GPU sharing (MIG and/or vGPU time-slicing) for efficient GPU use across workloads

• Expose GPU and LLM workload metrics to Prometheus (e.g. DCGM exporter) with Grafana dashboards

• Validate AI components on the Kubernetes (VKS) platform

• Run and document scalability tests for GPU and storage clusters

Must have

• NVIDIA AI Enterprise on Kubernetes, including the NVIDIA GPU Operator and NIM deployment

• GPU sharing with MIG and/or vGPU time-slicing

• Kubernetes in production, including Helm

• GPU monitoring with Prometheus and Grafana (incl. DCGM exporter)

• Hands-on LLM inference serving and performance testing (NIM, Triton or vLLM)

• Active security clearance

• Fluent English, written and spoken

Nice to have

• VMware Private AI Foundation with NVIDIA

• NeMo Guardrails

• Vector databases (e.g. pgvector)

• VKS or vSphere with Tanzu

• NVIDIA AI infrastructure certification, CKA or CKAD

Please note: this is an infrastructure role. Data scientists / ML researchers focused on model development, and Kubernetes engineers without GPU experience, will not be a fit.

To apply, click Apply or email your CV to dhinakaran.b@ampstek.com