AI Compute Engineer

The role

AI Compute Architect 📍 Medellín, Colombia

We're building a next-generation AI infrastructure platform that delivers high-performance bare-metal GPU compute for large-scale AI training and inference.

As our AI Compute Architect, you'll lead the architecture, qualification, and operational readiness of our GPU infrastructure across rapidly scaling data centers. You'll make the platform work as an integrated production system that connects GPU servers, firmware, OS, NVIDIA software, high-performance fabrics, storage, provisioning, scheduling, observability, and on-site operations.

What you will do

Define the architecture: Set lifecycle standards for NVIDIA HGX platforms and validated baselines for firmware, BIOS, BMC, OS, drivers, CUDA, and NCCL. Own compatibility requirements and the model of GPU/CPU/memory/PCIe/NVLink/NVSwitch/NIC/storage relationships. Decide what testing each platform change requires before production.
Lead qualification and burn-in: Design the strategy for new clusters, new GPU platforms, repaired nodes, and major changes. That includes load profiles, duration, coverage, and pass criteria. Analyze fleet-wide distributions and outliers to separate isolated failures from systemic issues in hardware, firmware, software, topology, power, thermals, or test configuration.
Diagnose health and performance: Interpret NVIDIA diagnostics and telemetry, covering GPU, NVLink, NVSwitch, PCIe, memory, network, thermal, and power signals. Lead root-cause analysis for intermittent, multi-node, and fleet-wide issues, including collective and point-to-point communication problems.
Validate with real workloads: Define representative training and inference workloads, including dense, MoE, and different parallelism strategies. Set reproducible baselines for throughput, scaling, latency, and numerical behavior, and pinpoint whether degradation comes from compute, communication, storage, scheduling, or configuration.
Integrate across domains: Work with Network (topology, GPU-to-NIC locality, RDMA), Storage (access, checkpointing, recovery), Platform/DevOps (scheduler, containers, provisioning), and Facilities (power, thermal correlation). Route issues to the right specialists with solid evidence.
Own operational readiness and acceptance: Define health, readiness, quarantine, and return-to-service gates. Guide automation teams in building reproducible workflows and interpret their results. Translate customer requirements into validation strategies, rule platforms ready, degraded, conditional, or unsuitable, define remediation and re-test scope, and communicate risks to engineering, vendors, customers, and leadership.

AI Compute Engineer

The role

AI Compute Engineer

The role

What you will do

What you need

Nice to have

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