AI Adoption Lead for ASIC Design & Verification

Ciena; Ottawa; On-site; CAD 109,000 - 174,000; Full time

Benefits offered by this job

Medical benefits

Dental benefits

Vision benefits

401(k) plan

ESPP

EAP

Paid holidays

Paid vacation

Job summary

Ciena is seeking an AI Champion to lead the practical adoption of AI across ASIC engineering workflows in Ottawa. The role focuses on scalable AI-driven methodologies that improve productivity, quality, and IP protection, while maintaining disciplined validation standards.

The position requires collaboration with design, verification, and physical implementation teams, prioritizing high-impact AI applications and mentoring engineers in AI-enabled workflows.

Qualifications

• 5+ years in ASIC design, verification, or physical design environments.
• 2+ years in applying AI agents and skills in engineering workflows.
• Experience delivering presentations to management audiences.
• Application of project management practices to support structured and disciplined workflows.

Responsibilities

• Drive adoption of AI across ASIC design, verification, and physical design workflows.
• Create and implement AI use cases for RTL design, verification, scripting, documentation, and regression analysis.
• Develop guidance, workflows, and guardrails to enable pragmatic and repeatable AI adoption.
• Evaluate and integrate AI tools, applications, and agentic workflows from internal teams and external vendors.
• Establish standardized methodologies for developing reusable AI agents and skills.
• Collaborate with engineering, CAD, IT, and methodology teams to prioritize and deploy high‑value AI applications.
• Mentor engineering teams on AI‑enabled workflows and promote sharing of outcomes, learnings, and best practices.

Skills

ASIC design experience

AI agents in engineering

Presentation to management

Project management practices

Job description

Ciena is seeking an AI Champion to lead the practical adoption of AI across ASIC engineering workflows in Ottawa. The role focuses on scalable AI-driven methodologies that improve productivity, quality, and IP protection, while maintaining disciplined validation standards.

The position requires collaboration with design, verification, and physical implementation teams, prioritizing high-impact AI applications and mentoring engineers in AI-enabled workflows.