Sr. PIC Platform Engineer

About Arycs Technologies

Arycs delivers power-efficient, coherent-class optical connectivity based on silicon photonics, coherent DSP, and advanced optical architectures. Our solutions provide industry-leading bandwidth per watt, deterministic performance, and flexible network evolution for AI, cloud, telecom, and edge infrastructure. Designed for real world deployment, Arycs Technologies enables networks to scale with growing AI demand without disruptive redesign or hardware replacement.

We are seeking a Silicon Photonics PIC Platform Engineer to lead engagement with external silicon photonics foundries and backend manufacturing partners in support of advanced photonic integrated circuits (PICs). This role will be responsible for working closely with foundries as they develop and mature their fabrication processes, translating process capabilities into product requirements, driving qualification activities, and enabling a path to high-volume manufacturing.

The ideal candidate combines strong process expertise with experience in photonic integrated circuits, data-driven problem‑solving skills, and the ability to collaborate effectively across internal engineering teams and external manufacturing partners.

• Foundry & Backend Engagement
  • Lead technical engagement with silicon photonics foundries and wafer backend partners across the full process lifecycle, including process development, yield ramp, and high-volume manufacturing readiness.
  • Establish strong working relationships and communication cadence to enable rapid issue resolution and effective escalation management.
• New Product Introduction (NPI)
  • Drive NPI for silicon photonics PICs from early process development through production release.
  • Ensure foundry and backend process capabilities meet optical, electrical, reliability, and manufacturability requirements.
• Yield & Process Optimization
  • Monitor wafer fabrication and backend yield performance using data-driven methodologies.
  • Identify systematic process issues and lead structured root cause analysis (RCA), corrective actions, and continuous improvement initiatives.
• Cross-Functional Collaboration
  • Partner closely with PIC Design, Product Development, Test Engineering, Reliability, and Operations teams.
  • Support process characterization, failure analysis, design-for-manufacturability (DFM), and performance optimization efforts.
• Cost & Efficiency Improvement
  • Support cost reduction initiatives, including wafer utilization optimization, process simplification, cycle time reduction, and backend efficiency improvements.
  • Drive yield improvement programs to improve cost per die and overall manufacturing efficiency.
• Supplier & Performance Management
  • Define, monitor, and report key supplier metrics such as yield, defectivity, process variation, cycle time, and cost.
  • Provide regular updates, including risk assessments and mitigation plans, to internal stakeholders.
• Process Qualification & Reliability
  • Lead or support process qualification and reliability validation aligned with industry standards (Telcordia, JEDEC, IPC, and semiconductor manufacturing standards).
  • Ensure robust process control and long-term reliability of silicon photonics products.

• Education
  • Bachelor’s, Master’s, or PhD in Electrical Engineering, Materials Science, Physics, or related field.
• Experience
  • 5+ years (or equivalent) in semiconductor process engineering, yield engineering, or foundry interface roles.
  • Direct experience with silicon photonics, CMOS, or advanced semiconductor fabrication strongly preferred.
• Technical Skills
  • Strong understanding of wafer fabrication processes (lithography, etch, deposition, CMP) and backend processing.
  • Experience with yield analysis, SPC, DOE, and root cause methodologies (e.g., 8D, Fishbone, Pareto).
  • Familiarity with reliability standards (Telcordia, JEDEC) and qualification methodologies.
  • Ability to interpret optical and electrical performance data and correlate to process variations.
• Tools & Methods
  • Experience with statistical analysis tools (JMP, Python, MATLAB, etc.).
  • Knowledge of failure analysis techniques and manufacturing data systems.
• Soft Skills
  • Excellent cross-functional…