An IT infrastructure solutions and services providerHiring

AI Infrastructure Consulting Engineer, Converged Compute & Storage

  • Remote, United States
  • Mid-level
  • Posted 12 days ago
Apply with Keywordise AI

or apply from Claude / ChatGPT / Muse

In one line

Client-facing consulting engineer who designs and stands up GPU compute and high-performance storage for enterprise AI workloads, with travel to customer sites.

About the role

Enterprise AI and machine learning workloads need accelerated compute, fast storage and reliable data movement to work together. This billable role turns client requirements into validated infrastructure and hands over working systems.

At a glance

Pay
Not stated in the posting
Remote scope
Remote, United States
Seniority
Mid-level
Skills
NVIDIA DGX, HGX, NFS, SMB, NVMe, Linux, Kubernetes, Slurm
Posted
23 Oct 2026
Last checked
3 Nov 2026

What you will do

  • Implement and integrate GPU compute and high-performance storage for training, fine-tuning, inference and data-heavy work
  • Track time and expenses against the statement of work, flagging scope, schedule or budget risks early
  • Work with project managers, architects, sales, partners and client stakeholders on dependencies, risks and timelines

What they look for

  • Bachelor's degree plus 3 years delivering complex infrastructure projects, or 7 years of that experience without a degree
  • Hands-on history installing, upgrading, configuring and troubleshooting enterprise compute and storage
  • Familiarity with NVIDIA DGX, HGX or similar GPU systems, and with AI workload stages from data ingest to inference
  • Knowledge of scale-out and high-performance storage: NFS, SMB, object storage, parallel file systems, NVMe
  • Linux administration skills covering firmware, drivers, health checks and performance debugging
  • Able to write and run implementation and test plans, document work and explain it to leadership and clients

Nice to have

  • Experience with NVIDIA AI Enterprise validated architectures and dependencies
  • Familiarity with GPUDirect Storage, RDMA, Kubernetes, Slurm or container runtimes

How Keywordise applies for you

  1. 1Upload your CVAdd your CV once. It takes about a minute.
  2. 2Tailored to this jobKeywordise writes a CV and a cover letter for this job from your real experience.
  3. 3The form fills itselfName, email, experience and screening questions, field by field.
  4. 4Application sentYou get a receipt and follow it in your dashboard.

Apply with Keywordise AI7-day free trial, no card.

Apply from your AI assistant

Connect Keywordise to your assistant once, then send it the prompt. It applies for you.

ClaudeConnectorChatGPTConnectorMuseby Meta

Claude

  1. In Claude, open Settings, then Connectors, and choose Add custom connector.
  2. Name it Keywordise and paste the connector URL.
  3. Click Connect, log in to Keywordise and approve. Then send the prompt in a new chat.
Connector URL
https://keywordise.com/mcp

Disconnect any time in your Keywordise settings.

ChatGPT

  1. In ChatGPT, open Settings, then Connectors. On plans that need it, turn on developer mode first.
  2. Add a new connector with the connector URL and choose OAuth. Leave the client ID and secret empty.
  3. Log in to Keywordise and approve. Then send the prompt in a new chat.
Connector URL
https://keywordise.com/mcp

Disconnect any time in your Keywordise settings.

Muse

  1. Open Muse (muse.ai or the app) and send it the message below.
  2. If Muse asks how to sign in, answer OAuth. Open the sign-in link it sends, log in to Keywordise and approve.
  3. Send the prompt. Muse asks before it sends anything.
Message for Muse
Add a custom connector called Keywordise. It is a remote MCP server at https://keywordise.com/mcp and uses OAuth. Give me the sign-in link.

Muse is available in the US only for now.

Prompt
Apply to Keywordise job v4v7u3lefy
How to connect

Questions about this job

Is this a remote job, and where can I work from?

The posting lists it as remote for people in the United States.

What does this job pay?

No pay range is stated in the posting.

What experience is needed?

It is a mid-level role. The posting asks for: bachelor's degree plus 3 years delivering complex infrastructure projects, or 7 years of that experience without a degree; hands-on history installing, upgrading, configuring and troubleshooting enterprise compute and storage; familiarity with NVIDIA DGX, HGX or similar GPU systems, and with AI workload stages from data ingest to inference. Skills it names include NVIDIA DGX, HGX, NFS, SMB.

How do I apply with Keywordise AI?

Press the Apply with Keywordise AI button and add your CV. Keywordise tailors your CV and cover letter to this posting and sends the application for you, with a free 7-day trial and no card.

More remote IT and software jobs

All remote IT and software jobs
An IT infrastructure solutions and services providerRemote, United States
Apply with Keywordise AI