<div>Nava is a neocloud company purpose-built for the AI era. We design, deploy, and operate large-scale GPU infrastructure and deliver inference-as-a-service to teams building the next generation of AI products. Our platform runs on NVIDIA GPU systems, high-performance RDMA fabrics, and a fully automated, software-defined operations model. Every engineer at Nava works close to the metal, on infrastructure built to keep GPUs saturated and models serving.</div><div> </div>

Nava

About Nava
Nava is a neocloud company purpose-built for the AI era. We design, deploy, and operate large-scale GPU infrastructure and deliver inference-as-a-service to teams building the next generation of AI products. Our platform runs on NVIDIA GPU systems, high-performance RDMA fabrics, and a fully automated, software-defined operations model. Every engineer at Nava works close to the metal, on infrastructure built to keep GPUs saturated and models serving.
About the Role
Lead end-to-end delivery of large-scale GPU infrastructure—from infrastructure readiness through deployment, validation, and production handover. Own timelines, cross-functional coordination, vendor execution, risk management, acceptance milestones, and customer delivery commitments.
What You’ll Do
<ul>
<li>Build and own the integrated master delivery plan—including critical path, milestones, dependencies, and acceptance gates—for each new GPU cluster.</li>
<li>Coordinate site operations, power and cooling readiness, logistics, OEM delivery, rack installation, network deployment, compute/storage bring-up, security, and platform teams.</li>
<li>Lead weekly milestone governance, executive reviews, issue and decision tracking, delivery risk management, and recovery planning.</li>
<li>Own delivery partner governance across colocation providers, OEMs, integrators, and key suppliers; resolve dependency and schedule conflicts.</li>
<li>Collaborate with technical owners to plan GPU diagnostics, burn-in, network/storage benchmarks, reliability testing, and customer acceptance evidence.</li>
<li>Escalate blockers early with clear options, business implications, assigned owners, and deadlines—ensuring committed dates are backed by evidence.</li>
<li>Run formal production-readiness and operational handover—including inventory, as-built documentation, known issues, runbooks, and support ownership.</li>
</ul>
What You’ll Need
<ul>
<li>10–15 years of experience in top-tier consulting (e.g., MBB), with a focus on technology transformations, tech strategy, roadmap development, and technical program management.</li>
<li>Demonstrated success leading large, cross-functional, multi-vendor programs with firm deadlines, budgets, interdependencies, and measurable outcomes.</li>
<li>Strong program decomposition, critical-path management, risk mitigation, structured problem-solving, and executive-level communication skills.</li>
<li>Ability to reason effectively about GPU servers, networking, storage, data center commissioning, and acceptance—even when specialist teams own the technical execution.</li>
<li>Proven experience engaging with OEMs, data center providers, delivery leadership, and senior stakeholders.</li>
<li>Experience deploying and validating cloud regions, hyperscale facilities, AI/HPC clusters, or other hardware-intensive production platforms.</li>
<li>Hands-on exposure to GPU or AI-focused datacenter operations.</li>
</ul>