Global Enterprise AI Solutions Architect – NVIDIA AI Data Platform

Posted One Month Ago
Be an Early Applicant
Hiring Remotely in CA
Remote
250K-300K Annually
Senior level
Big Data
The Role
Own the technical sales motion for NVIDIA-focused enterprise AI infrastructure deals. Lead discovery, architecture, proof-of-concept design and execution, technical closes, partner and field SE enablement, troubleshooting, escalation, customer workshops, and product feedback. The role requires expertise in NVIDIA systems, storage, data platforms, Linux, parallel file environments, GPU clusters, and AI pipelines, with Bay Area availability for on-site partner or customer sessions.
Summary Generated by Built In

Hammerspace is a fast-growing software company building the data foundation for the AI era. We are changing how organizations access, move, and use unstructured data by eliminating data silos and creating a single, high-performance data environment across sites, clouds, and storage systems. This ensures AI, GPUs, HPC, and data-intensive applications can operate at full speed.

 

Our technology combines a high-performance parallel global file system with intelligent data orchestration to make data available wherever compute needs it, without disruptive migrations or infrastructure lock-in. The result is faster AI pipelines, higher GPU utilization, quicker time-to-insight, and a radically simpler way for researchers, developers, and enterprises to put their data to work.


About the role


Hammerspace is seeking a senior, customer-facing Global Enterprise AI Solutions Architect, Working hand in hand with the Global Enterprise Sales Executive, you will accelerate the adoption of the Hammerspace NVIDIA AI Data Platform (AIDP) with large enterprise customers worldwide.

 

This individual will position Hammerspace as the data foundation for enterprise AI—making distributed, unstructured data across on-premises, cloud, edge, and heterogeneous storage environments accessible, governed, searchable, and ready for AI. The focus includes Retrieval-Augmented Generation (RAG), enterprise search, agentic AI, AI copilots, knowledge management, research assistants, model development, inference, and AI data pipelines.

 

You will own the technical work on those deals: POCs, the architecture that sits on NVIDIA systems, and the software stack where it meets the Hammerspace data path.

 

What you will do

  • Own solution architecture for AI opportunities across three motions: NVIDIA ecosystem, AI neoclouds, and enterprise AI.
  • Lead technical discovery, reference designs, and POCs that put Hammerspace on the critical path for GPU clusters and AI factories.
  • Sit with NVIDIA, neocloud, and enterprise AI architects and SEs without a translator — data path, parallelism, locality, and operational reality.
  • Enable Hammerspace Field and partner teams to run routine AI-path POCs and designs without escalating every engagement.
  • Pull Field CTO hardware-partner or HPC architecture when the problem needs that specialty; escalate to the Director when a POC, severity issue, or coverage gap is stuck.
  • Feed Product real gaps from NVIDIA, neocloud, and enterprise AI deployments.
  • Hand off pure commercial alliance or partner-program work to Partner Enablement; hand off product messaging to Presales.
What good looks like in six months
  • AI deals in flight across NVIDIA, neocloud, and enterprise AI have a named solutions architect.
  • Routine AI-path technical work does not consume Field CTO capacity.
  • Partners and Field can run a routine AI POC or reference design without you on every call.
  • Stuck POCs, architecture blockers, severity issues, and coverage gaps reach the Director the same day.
  • You know when to finish it yourself, when to pull a Field CTO specialty, and when to escalate.
What you bring

Required

  • Experience as a solutions architect or senior SE on AI / GPU infrastructure deals
  • Depth in at least one of: NVIDIA ecosystem, AI neocloud platforms, or enterprise AI platforms — and fluency to work across all three
  • Ability to run an AI-path POC end to end (data path, performance, operational handoff)
  • Comfort with GPU-centric architectures: training/inference pipelines, checkpoints, high-throughput file/object access, multi-site data

Preferred

  • Direct work with NVIDIA partner or customer field organizations
  • Neocloud or GPU-cloud deployment experience
  • Enterprise AI platform engagements (MLOps, feature/training stores, model factories)
  • Storage or data-platform background adjacent to AI clusters
  • Experience enabling field teams and partner SEs to run without you in the room

You do not need to match every bullet. AI Solutions Architect here is a global motion across NVIDIA, neocloud, and enterprise AI — not a single logo or a single theater.

What this role does not own
  • Field CTO hardware-partner or HPC architecture ownership worldwide
  • Partner or channel program design, partner tiering, or enablement calendar (Partner Enablement)
  • Product narrative and use-case marketing (Presales)
  • New-logo development (Customer Research)
  • Sales quota
  • Hardware-partner specialist coverage for general OEM / appliance motions (separate Specialist SE openings)


To the extent required by state or local hiring regulations, we will consider for employment any qualified applicant, including those with arrest and conviction records, in a manner consistent with the applicable regulation.
The anticipated base salary range for this role is $250,000-300,000OTE.  Actual compensation will be determined by several factors including, but not limited to, level of professional/education experience, skills/abilities, internal equity, and budgetary considerations. In addition, Hammerspace offers a broad range of health plans for medical, dental, vision, life and disability. We also offer 401k plans and flexible time off. Applications will be accepted until the position is filled.
Hammerspace is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, gender, religion, sex, sexual orientation, age, disability, military status, or national origin or any other characteristic protected under federal, state, or applicable local law.

Notice to Recruiters and Staffing Agencies:
Agencies are hereby specifically directed not to contact Hammerspace employees directly in an attempt to present candidates. To protect the interests of all parties, Hammerspace will not accept unsolicited resumes from any source other than directly from a candidate. Any unsolicited resumes sent to Hammerspace will be considered Hammerspace property. Hammerspace will not pay a fee for any placement resulting from the receipt of an unsolicited resume. Hammerspace will consider any candidate for whom an Agency has submitted an unsolicited resume to have been referred by the Agency free of any charges or fees.  Agency must obtain advance written approval from Hammerspace’s recruiting function to submit resumes, and then only in conjunction with a valid fully-executed contract for service and in response to a specific job opening. Hammerspace will not pay a fee to any Agency that does not have such agreement in place.

 

 

Skills Required

  • Proven experience as the technical owner on NVIDIA-path infrastructure deals involving GPU systems, partner sales engineers, and joint proofs of concept
  • Ability to collaborate directly with NVIDIA sales engineers and architects
  • Ability to run proofs of concept end-to-end and teach partner or field sales engineers to do the same
  • Five or more years of experience in pre-sales, solutions engineering, or comparable technical sales roles in storage, data management, or accelerated computing infrastructure
  • Working knowledge of Linux, NFS, pNFS or parallel file environments, and how data platforms attach to GPU clusters
  • Availability to work in the Bay Area
  • Clear written and verbal communication with partner sales engineers, customer architects, and field teams
  • Experience with the NVIDIA partner motion at a storage, data, or systems company
  • Understanding of distinguishing hardware, software, and commercial problems
  • Familiarity with NVIDIA networking and software stack components, including drivers, runtimes, fabrics, and scheduling
  • Experience with AI or GPU training and inference pipelines
  • Experience with AWS, Azure, or Google Cloud
  • Knowledge of NAS, SAN, object storage, and parallel file architectures
  • Knowledge of container and Kubernetes environments
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The Company
HQ: San Mateo, CA

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