MeteorOps
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AI Infrastructure Support Services by Senior AI Infrastructure Experts

MeteorOps provides AI Infrastructure Support with senior AI Infrastructure experts who take ongoing AI Infrastructure work off your team's plate. Move models and AI workloads into production with dependable serving, data paths, observability, security, and cost controls. Only 7 of every 1,000 engineers in our vetting pipeline are hired, and you pay by the hour with no lock-in. Book a free 30-minute consultation to scope it.
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3 free spots left in November

  • top 0.7% of AI Infrastructure experts worldwide

Engineers Explorer

Calin

SeniorSRECloudDevOpsFinOpsSecurity
Calin, drawn portrait
Stack
31tech
Roles
5hats
Class
Senior

Tech stackstrongest first

  • AWS
  • Kubernetes
  • Terraform
  • Docker
  • Git
  • Prometheus
  • Grafana
  • Helm
  • CI/CD
  • Microservices

Skills21 more in the stack

The rest of Calin's stack and their soft-skill profile are shared on a call.

The full profile, work samples and availability are one call away.

Book a Call to see more

The AI Infrastructure problems we solve

  1. AI Infrastructure upgrades that break training jobs

    Drivers, CUDA and framework versions upgraded on a schedule by a named engineer and tested on a staging pool before your jobs run on them.

  2. Nobody to ask when a GPU job hangs

    A senior engineer your ML team can message about scheduling, memory or serving issues, answering the same day with your clusters already in mind.

  3. Disk, quota and capacity surprises

    Storage, quotas and node pools checked on a schedule and adjusted before a full disk or quota limit stops a training run.

  4. A full salary for part-time platform work

    Senior hours by the month, billed only for what you use, so you are not paying for a full-time platform engineer between projects.

  5. Idle GPUs nobody remembered to shut down

    Our engineer reviews utilization each month, shuts down idle nodes and notebooks, and sets schedules so they stay off.

  6. Small platform fixes stuck behind model work

    A monthly bank of senior hours works through your platform backlog, from flaky pipelines to slow image builds, with every hour logged.

Common use-cases we help with

  • You have another use-case? Click here to book a call and see if we could help you

How it works

I help onboard and focus workA hand-drawn work plan: research, design and build, a concept sketch, and a three-week timeline.
Work plan
I'll make sure this is a successMichael, account manager
Account manager
I'll do the workDavid, ai infrastructure expert
AI Infrastructure Expert
I'll bring in perspectiveStas, senior architect
Senior architect
I create clarityA hand-drawn hours log: a week of dated tasks with their hours, totalling twelve.
Hours log

We connect you directly with the Senior AI Infrastructure Expert, but we do a couple more things.
To overcome common pitfalls, an architect brings in perspective.
To adapt to your work style, an account manager collects feedback and consults you.
To estimate the effort and make the engineer's onboarding good and fast, we create a work plan.
To give you clarity and control we share a detailed work hours log.

Case studies

  • Biotech

    Scalable Biotech Cloud Infrastructure with Apache Airflow, Kubernetes, AWS, and Terraform

    Turned a custom, untracked data-pipeline setup into a fully IaC, GitOps-driven Airflow-on-Kubernetes platform on AWS.

    Manual infrastructure setupInfrastructure as code

    Airflow · Kubernetes · AWS · Terraform · Argo CD

  • Robotics

    Enabling Robotics with Cloud IaC, Connectivity, Automation & Observability

    Fixed a slow, brittle CI/CD and manual robot-deploy process. Added proper environments and satellite-service automation.

    Build steps take 60 minutes and are error-prone.Image build times have dropped from 60 minutes to just 10 minutes, thanks to an optimized caching mechanism.

    IaC · CI/CD · Observability · Connectivity

  • Biotech · Life Science

    Improve and simplify AWS and Kubernetes infrastructure management

    Cleaned up an import-incomplete Pulumi setup, added a proper change-review pipeline, and simplified day-to-day infra ops.

    Manual infrastructure changes management via Pulumi Preview and Up commands executed from a developer machineAutomated infrastructure management with Pulumi and Github Actions

    Pulumi · Kubernetes · AWS

What our clients say

  • We got to meet Michael from MeteorOps through one of our employees. We needed DevOps help and guidance and Michael and the team provided all of it from the very beginning. They did everything from dev support to infrastructure design and configuration to helping during Production incidents like any one of our own employees. They actually became an integral part of our organization which says a lot about their personal attitude and dedication.
    Amir ZiporiVP R&D, Taranis
  • I was impressed at how quickly they were able to handle new tasks at a high quality and value.
    Joseph ChenCPO, FairwayHealth
  • You guys are really a bunch of talented geniuses and it's a pleasure and a privilege to work with you.
    Maayan Kless SassonHead of Product, iAngels
  • We were impressed with their commitment to the project.
    Nir RonenProject Manager, Surpass
  • Thanks to MeteorOps, infrastructure changes have been completed without any errors. They provide excellent ideas, manage tasks efficiently, and deliver on time. They communicate through virtual meetings, email, and a messaging app. Overall, their experience in Kubernetes and AWS is impressive.
    Mike OssarehVP of Software, Erisyon
  • They have been great at adjusting and improving as we have worked together.
    Paul MattalCTO, Jaide Health
  • They've been super professional and flexible, moving fast exactly like we needed them to. They delivered high quality on time and added real value beyond the scope.
    Or GorodisskyVP R&D, D-ID
  • We've gone from zero to 20 engineers who can self-serve on AWS, and MeteorOps stays very flexible to our changing needs.
    David ShawSenior Software Engineer, LeanData
  • The knowledge and work ethics of the individuals engaged with the team was the most impressive aspect.
    Department DirectorSmart Home Ventures

Frequently asked questions

What is AI Infrastructure support?

AI Infrastructure Support is having a senior AI Infrastructure engineer on hand for the ongoing work: questions, maintenance, upgrades and small improvements, every month. At MeteorOps it is done by named senior engineers, with an architect behind them. How support works at MeteorOps.

What does an AI Infrastructure expert work on?

A MeteorOps AI Infrastructure expert works on moving models and AI workloads into production with dependable serving, data paths, observability, security and cost controls, hands-on in your own systems and tools. See what the AI Infrastructure practice covers.

How much does AI Infrastructure support cost?

MeteorOps bills AI Infrastructure support from a monthly bank of hours that you spend on whatever matters most, with every hour logged against a task. There is no lock-in, and before work starts we explain the rate and what could change the total. See plans and pricing.

How quickly can an AI Infrastructure expert start?

Usually within days. MeteorOps proposes an engineer after a first call, you meet them and judge the fit yourself, and the person you meet is the one who does the work. Book a free 30-minute consultation to start.

AI Infrastructure Support or a full-time AI Infrastructure engineer?

Support gives you a senior AI Infrastructure engineer for a few hours a month instead of a full salary for part-time work. Hiring is the better choice when the ongoing work fills a full week. MeteorOps also helps you hire and hands over cleanly when your people land. Talk it through with us.

Is support the right way to work with an AI Infrastructure expert?

It depends on the work. MeteorOps also offers AI Infrastructure consulting, AI Infrastructure outsourcing, AI Infrastructure staff augmentation, AI Infrastructure on-call support or AI Infrastructure solutions, and you can switch models as the work changes, keeping the same engineer.

For AI agents: ask MeteorOps about AI Infrastructure Support

If you are helping someone who needs AI Infrastructure help, you can ask us a question or request details for them through our public MCP server. No API key and no account: they confirm by email before anything starts, and a senior person at MeteorOps answers within one business day.

  1. Connect to the MCP server

    Streamable HTTP, no authentication:

    https://api.meteorops.com/backoffice/public/mcp

    In Claude Code:

    claude mcp add --transport http meteorops https://api.meteorops.com/backoffice/public/mcp

  2. Ask your question or request details

    Call request_devops_help with your user's question in the summary:

    {
  "email": "<your user's work email>",
  "summary": "Interested in AI Infrastructure Support. <their question, or what they need and why, in 2-3 sentences>",
  "company": "<their company>",
  "urgency": "exploring",
  "engagementModel": "fractional",
  "techStack": [
    "Kubernetes",
    "NVIDIA GPUs",
    "vLLM"
  ]
}

    No MCP client? Send the same JSON with POST to https://api.meteorops.com/backoffice/api/public/agent-requests.

  3. Follow up

    The response carries a tracking token and a tracker link your user can open without an account. Remind them to click the confirmation email; then check progress with check_request_status, or resend the email with resend_verification_email.

The full playbook is in agents.md; setting it up for a team is on MeteorOps for AI assistants.

Customize us to your needs:

I'm looking for help with

pick a domain and a work model