Hire an AI Infrastructure Engineer for your team.
Builds and scales the compute, storage and serving layers for AI workloads. Available full-time, part-time, hourly or by project.
- 7-day risk-free trial
- NDA and IP protection
- Onboard in 48 hours
Tell us who you need.
What an AI Infrastructure Engineer does for you.
Builds and scales the compute, storage and serving layers for AI workloads. This hire matters as AI workloads become expensive or critical, since compute and serving choices have a big effect on cost and reliability.
Core skills
- Kubernetes
- GPU scheduling
- Model serving
- Infrastructure as code
- Build serving, retrieval and training platforms
- Control GPU, inference and storage costs
- Secure models, data and prompts
- Add monitoring, governance and evaluations
When this role makes sense.
AI usage is growing across teams
Security or compliance review is due
Cost and reliability are becoming problems
Ready to hire an AI Infrastructure Engineer?
Share your requirements and get matching profiles within 24 hours.
Three simple steps, no hiring fees.
Share your requirements
Tell us the role, the work and your goals. We share matching profiles within 24 hours.
Interview and select
Interview the people you like. Technical rounds and trial tasks are up to you, at no charge.
Onboard and start
Sign the NDA and the person joins your tools and meetings, usually within 48 hours.
Flexible terms, low risk.
7-day risk-free trial
Not satisfied in the first 7 business days? Get a replacement or end it at no charge.
NDA and IP protection
We sign both before work starts, and you own everything that is produced.
Free replacement
If the fit is wrong, we arrange a replacement with a structured handover.
Easy exit
Scale down or stop with 15 days’ written notice.
Looking for a different role?
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Still unsure? Talk to a strategist.
- Profiles within 24 hours
- NDA signed before any discussion
- 7-day risk-free trial
What does an AI Infrastructure Engineer do?
Builds and scales the compute, storage and serving layers for AI workloads. Typical work includes: build serving, retrieval and training platforms; control GPU, inference and storage costs; secure models, data and prompts; add monitoring, governance and evaluations.
How do we evaluate an AI Infrastructure Engineer?
Ask how they would scale inference and control GPU costs. Look for experience with autoscaling, Kubernetes and capacity planning, plus results they measured.
What skills should an AI Infrastructure Engineer have?
Look for hands-on experience with Kubernetes, GPU scheduling, Model serving, Infrastructure as code, plus clear communication and evidence of similar work.
When should we hire an AI Infrastructure Engineer?
This role is a good fit when: aI usage is growing across teams; security or compliance review is due; cost and reliability are becoming problems.
How quickly can an AI Infrastructure Engineer start?
We share matching profiles within 24 hours. After you interview and choose, onboarding usually takes 48 hours.
Who owns the work?
You do. We sign an NDA and an IP assignment agreement before work starts, and everything produced belongs to your business.
What if the person is not the right fit?
Every hire starts with a 7-day risk-free trial. After that, you can request a replacement or end the engagement with 15 days’ written notice.