AI Lead Architect for Chip Design Excellence

191 Altera Corporation; San Jose (CA); On-site; USD 206,000 - 303,000; Full time

Job summary

Altera is seeking an AI Lead in HW Engineering to define and drive the company's AI strategy for chip design and to lead its deployment into design, verification, and implementation workflows.

This senior, individual-contributor role requires deep hardware/EDA credibility and the ability to act as a change agent—identifying where AI can accelerate development, building the case for adoption, and partnering with engineering teams across design, verification, and signoff.

Qualifications

• 12+ years of hands-on hardware design, verification, or implementation experience.
• Deep familiarity with EDA tools and flows.
• Experience applying AI/ML to engineering workflows.
• Proficient in Python and ML/LLM tooling.
• Strong communication and leadership without formal management.
• BS/MS/PhD or equivalent practical experience.

Responsibilities

• Define AI strategy for hardware design, verification, and implementation.
• Lead deployment of AI-driven tools into production design, verification, and implementation flows.
• Build and own AI tooling stack for design teams (design collateral, telemetry, etc.).
• Own evaluation and operational discipline for AI tools and adoption decisions.
• Mentor and uplift AI/ML fluency across engineering teams.

Skills

Python proficiency

AI/ML techniques

Stakeholder communication

Cross-functional collaboration

Education

BS/MS/PhD in Electrical Engineering / Computer Engineering / Computer Science or related field

Tools

ML/LLM tooling

Retrieval-augmented generation

Agentic frameworks and tool use

LLM fine-tuning or post-training

Job description

Altera is seeking an AI Lead in HW Engineering to define and drive the company's AI strategy for chip design and to lead its deployment into design, verification, and implementation workflows.

This senior, individual-contributor role requires deep hardware/EDA credibility and the ability to act as a change agent—identifying where AI can accelerate development, building the case for adoption, and partnering with engineering teams across design, verification, and signoff.