Design, Test & Quality Hardware Lead
Role Overview
The role defines hardware qualification standards and ensures products pass established tests before customer shipment.
The lead investigates returned units and owns determining why failures occurred.
Key Skills for This Role
Full Job Posting
About Think AI
Think AI, founded in Riyadh in 2025, designs compute hardware and orchestration software together to improve compute efficiency.
Its mission is to build an efficient AI compute platform through co-development of hardware and software.
Role overview
The role defines hardware qualification standards and ensures products pass established tests before customer shipment.
The lead investigates returned units and owns determining why failures occurred.
What you will do
- Own thermal, electrical, mechanical, environmental, and reliability qualification.
- Define acceptance criteria and test coverage for each SKU and revision.
- Build and operate test rigs, instrumentation, and data capture for qualification gates.
- Lead failure analysis and corrective actions, including FMEA and returned-unit teardown.
- Track field reliability and apply findings to design, manufacturing, and supplier decisions.
- Keep qualification records auditable for customer procurement reviews.
What you need
- At least 5 years in hardware test, quality, or reliability engineering.
- Have written qualification plans from scratch and defended them to customers or auditors.
- Experience with thermal, power, flow, and vibration instrumentation, data capture, and analysis.
- Apply root-cause analysis beyond identifying symptoms.
- Based in Riyadh or willing to relocate.
Nice to have
- Environmental or industrial qualification experience.
- Statistical process control and reliability modelling.
- Test automation and scripting.
What Think offers
- Meaningful ownership and impact at an early-stage deep-tech company building foundational technology in house.
- Competitive early-stage compensation and close collaboration with a small, senior team.
- Work on problems combining hardware, systems, and AI at scale.
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