FREE ACCESS
5,000–10,000 jobs/day
See all jobs on Scoutfield
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates deep technical expertise in AI infrastructure, high-performance computing, and large-scale GPU systems, while effectively communicating complex ideas to diverse audiences. Proven ability to lead technical engagements, drive product integrations, and support customer success through scalable architecture design and deployment.
Highest-signal resume keywords
AI Infrastructure ExpertiseHigh-Performance ComputingNVIDIA GPU FamiliaritySolutions ArchitectureTechnical Partnerships
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Software EngineeringHardware EngineeringData Center DeploymentAI/ML SystemsProduct ManagementTechnical EnablementIntegration MilestonesDeployment PlansTroubleshootingArchitectural Design
Soft Skills
Problem-SolvingIntellectual CuriosityCustomer Success CommitmentClear Communication
Tools & Technologies
NVIDIA SDKsAI Infrastructure PlatformsNetworking SolutionsDeployment Services
Certifications & Qualifications
Bachelor's DegreeMaster's Degree
Industry Keywords
OEMODMSystem IntegratorDeployment Partner EcosystemsField Engineering
About the role
Key responsibilities & impact- Serve as a trusted advisor on complex or large-scale customer workloads and map them to NVIDIA's technology stack
- Co-design scalable architectures with OEM and deployment partners
- Define technical direction, integration milestones, and deployment plans
- Design, validate, and support solutions for customer and partner success
- Identify gaps between partner needs and NVIDIA offerings
- Communicate insights that shape internal product and engineering priorities
- Lead technical engagements and troubleshoot complex issues
- Drive technical enablement and platform adoption
- Help developers and enterprises integrate NVIDIA SDKs, frameworks, and systems
- Partner with engineering and product teams on successful deployment and continuous improvement
- Lead AI Factory build execution engagements, technical readiness, deployment validation, and issue resolution
Requirements
What you’ll need- Bachelor's or Master's degree or equivalent experience in Computer Science, Engineering, or a related field
- 8+ years of professional experience spanning software/hardware engineering, developer relations, technical partnerships, solutions architecture, or product management
- 3-5+ years of direct, hands-on experience in AI infrastructure, data center deployment, or large-scale AI/HPC systems
- Deep technical expertise in high-performance computing, AI/ML, data center infrastructure, rack-scale AI infrastructure, or large-scale GPU systems
- Track record of driving product integrations and contributing to software and hardware platforms, systems, and libraries
- Ability to communicate complex technical ideas clearly to technical and non-technical audiences
- Strong problem-solving skills, intellectual curiosity, and commitment to helping customers succeed
- Experience working with OEM, ODM, system integrator, or deployment partner ecosystems
- Familiarity with NVIDIA GPU, networking, and AI infrastructure platforms
- Experience working with services, field engineering, professional services, manufacturing partners, or deployment services teams
- Travel required up to 50%
Benefits
Comp & perks- Equity
- Benefits 📊 Check your resume score for this job Improve your chances of getting an interview by checking your resume score before you apply. Check Resume Score