Manager, Solutions Architecture, AI Infrastructure Build Readiness

Nvidia

Confirmed live today High trust

Quick summary

Work type: On-site
Location: Santa Clara, CA
Salary: $224,000–$356,500 / yr
Employment: Full-time
Posted: 13 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $199k

This role $290k

$127k most similar roles pay here $381k

This role pays more than 96% of similar roles. Most pay $162,000–$235,750 — the shaded band above. At the midpoint, this role pays about $290k versus about $199k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 1391 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1116 roles with salary data.

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At a glance

TL;DR · Manager, Solutions Architecture, AI Infrastructure Build Readiness

Role Posting Log in to save

Manager, Solutions Architecture - AI Infrastructure Build Readiness leads the AI Factory Build Enablement function to bridge gaps between OEM factory execution and services handover. In this role, you will build and manage a team of Solutions Architects who assess OEM tools, experience, and deployment readiness for AI Factory build-outs. You will develop standardized readiness checklists, risk scoring, and engagement health monitoring while coordinating cross-functional workstreams across architecture, engineering, program, and partner-facing teams. The role requires expertise in data center infrastructure including compute, networking, storage, cabling, power, cooling, firmware, BMC, and Linux. You will translate complex technical requirements into readiness criteria to mitigate risks before deployment. This position addresses the challenge of replacing per-engagement fixes with standardized operating models for large-scale AI infrastructure, ensuring seamless transitions between manufacturing partners and downstream service teams in an accelerated computing environment.

Skills

AI Infrastructure HPC GPU Data Center Infrastructure Linux Networking Storage Firmware BMC NPI Systems Integration Accelerated Computing OEM Readiness

What you'll do

Lead the AI Factory Build Enablement function to bridge gaps between OEM factory execution and services handover.
Manage a team of Solutions Architects focused on assessing OEM tools, experience, and deployment readiness.
Develop and implement standardized operating models, including readiness checklists, capability assessments, and risk scoring.
Establish formal sign-off processes and criteria for transitioning projects from manufacturing to service teams.
Orchestrate cross-functional workstreams across architecture, engineering, program, and partner-facing teams to align on milestones.
Identify recurring technical gaps and drive structured corrective actions with internal and external partners.
Provide leadership visibility into readiness risks, mitigation plans, and critical blockers affecting AI Factory execution.

What we're looking for

BS, MS, or equivalent experience in Computer Science, Electrical/Computer Engineering, Systems Engineering, Physics, Mathematics, or a related technical field.
Experience in infrastructure architecture, data center deployment, AI/HPC systems, partner enablement, technical field engagement, or large-scale systems integration.
4+ years of experience leading a team.
Prior people leadership experience including hiring, coaching, developing, and directing technical ICs.
Strong understanding of data center infrastructure including compute, networking, storage, cabling, power, cooling, firmware/BMC, Linux, and deployment workflows.
Experience translating complex technical requirements into readiness criteria, partner checklists, acceptance gates, or operating processes.
Strong cross-functional leadership across architecture, engineering, program, field, account, and partner-facing organizations.
Executive-ready communication skills to summarize risk, readiness, tradeoffs, and decision asks for senior leaders.
Experience with AI Factory, accelerated computing, rack-scale AI infrastructure, large-scale GPU systems, or HPC deployments (preferred).
Experience working with OEM, ODM, system integrator, or deployment partner ecosystems (preferred).
Familiarity with NVIDIA GPU, networking, and AI infrastructure platforms (preferred).
Experience working with services, field engineering, professional services, manufacturing partners, or deployment services teams (preferred).
Background with recruiting, mentoring, and developing technical talent in field-facing, partner-facing, or infrastructure architecture organizations (preferred).