Principal Module and FA Lead

Xscape Photonics Inc; Santa Clara (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

Xscape Photonics is seeking a hardware failure analysis lead to own system-level FA during pre-production and early-volume phases. You will triage cross-domain failures, determine ownership, and convene the right team to drive resolution across mechanical, electrical, thermal, firmware, and photonics domains.

You’ll establish integration procedures and KPIs with NPI, guide root-cause investigations, and drive countermeasures to closure while ensuring clear handoffs to the CM transition.

Qualifications

• BS+15 / MS+12 / PhD+9 years in hardware failure analysis spanning multiple domains.
• Fluency across mechanical, electrical, thermal, firmware; photonics experience preferred.
• Proven record leading cross-domain root-cause investigations.

Responsibilities

• Own FA documentation and trend-tracking system.
• Lead structured root-cause investigations using fishbone analysis.
• Drive countermeasures to closure with accountable teams.
• Define handoff criteria to NPI for CM transition.
• Lead data analysis to verify root-cause hypotheses.

Skills

Root-cause investigations

Data analysis

DOE design experiments

Cross-domain leadership

Systems engineering

Education

Electrical/Mechanical/Physics/Optical Eng degree

Job description

About The Role

As Xscape Photonics scales to volume production, this role owns module integration and system-level failure analysis across mechanical, electrical, thermal, firmware, and optical/photonics domains during the pre-production and early-volume phases — before ownership transitions to the NPI team as manufacturing shifts to contract-manufacturing-driven high volume.

As Xscape Photonics scales to volume production, this role owns module integration and system-level failure triage: quickly diagnose issues that span multiple domains, determine ownership, and convene the right cross-functional team to drive resolution.

Own system-level integration of the module — ensuring mechanical, electrical, thermal, firmware, and optical/photonics subsystems come together to meet spec, and resolving integration-stage issues (fit, interface, tolerance stack‑up, cross‑domain interactions) before they surface as field or production failures.

Work with the NPI team to establish module integration procedures and KPIs — entry/exit criteria between build stages, integration test flow, and the metrics used to track integration health — so they carry forward cleanly as products move into CM-driven volume.

Partner with design engineers across mechanical, electrical, thermal, firmware, and optical/photonics to evaluate system‑level trade‑offs and diagnostics that guide failure analysis and debugging.

Lead structured root‑cause investigations using fishbone analysis and staged, resource‑aware design of experiments — screening designs to triage candidate variables before committing to full characterization runs.

Lead data analysis to verify root‑cause hypotheses, and drive countermeasures to closure — tracking implementation through to actual design or process changes by the accountable owning team, rather than treating a documented finding as the end state. Feed learnings forward into NPI's process‑refinement work to reduce repeat failure modes during the contract‑manufacturing transition.

Own the FA documentation and trend‑tracking system — build this from scratch, as no formal infrastructure exists yet.

Define and maintain clear handoff criteria to the NPI team as products transition from pre-production/small‑volume to CM‑driven high‑volume manufacturing.

What Success Looks Like

• Integration issues (fit, interface, tolerance stack‑up, cross‑domain interactions) are caught and resolved pre‑production, reducing the volume of cross‑domain failures that reach FA
• Module integration procedures and KPIs are established jointly with NPI and hold up across the pre‑production‑to‑volume transition, without needing to be re‑defined at handoff
• Faster time‑to‑root‑cause as the FA process matures, with a documentation/trend‑tracking system that catches repeat failure modes early
• Root causes reliably close the loop into real design or process changes — not findings that sit unimplemented
• Clean handoffs to NPI at the CM transition, with repeat failure modes declining over time as FA learnings inform NPI's process work

What You'll Need

• BS+15 / MS+12 / PhD+9 years in hardware failure analysis, systems engineering, or related root‑cause engineering roles. Degree in Electrical Engineering, Mechanical Engineering, Physics/Applied Physics, Materials Science, Optical Engineering, or related field. PhD candidates should demonstrate post‑degree industry experience spanning multiple engineering domains, not solely depth in a single research area.
• Working technical fluency across mechanical, electrical, thermal, and firmware domains; photonics/optical experience strongly preferred
• Demonstrated experience leading cross‑domain root‑cause investigations on coupled, multi‑variable failure modes — not siloed single‑domain diagnosis
• Hands‑on, methodical technical practice: personally runs test and measurement setups, and defaults to a repeatable, structured problem‑solving method under pressure rather than ad hoc troubleshooting
• Practical experience designing and prioritizing DOEs under real‑world constraints — limited samples, long test cycles, many candidate variables
• Comfortable building quick first‑principles models (thermal, electrical, mechanical) to test a hypothesis or narrow candidate variables before committing to physical test time — not dependent on physical data alone to build confidence
• Track record of closing the loop from root cause to actual design/process change and engineering change control, including standing up processes or infrastructure from scratch in an early‑stage or resource‑constrained environment

Nice to have

• Direct photonics/optical packaging experience (fiber coupling, wire‑bond/die‑attach processes, epoxy and encapsulation materials)
• Pragmatic judgment on depth vs. speed — knows when "good enough root cause + corrective action" beats chasing full certainty under schedule pressure
• Collaborative, root‑cause‑first mindset over a “quality enforcement” mindset