Senior Infrastructure Automation Engineer - Silicon Co-Design Group

What you'll be doing:

• Define clear vision and roadmap for productivity efficiency improvement solutions in alignment with business needs and drive execution from design through delivery.

• Lead cross-function engineering teams on project deliverables commitment to streamline the system design and verification process and workflow. You own the pipelines between tools.

• Build production-grade AI-assisted automation infrastructure for Silicon Co-Design use cases, including reliable orchestration, observability, evaluation, guardrails, and human-in-the-loop controls where needed.

• Drive Cross-function Collaboration with ASIC, SW, System Design, Product, Security, and Operations teams to ensure reliability, scalability, and performance, fostering a culture of technical excellence, collaboration, and ownership.

• Drive hard debugging and root-cause analysis across infrastructure, automation, data, and HW/SW boundary issues; separate competing hypotheses, define measurement plans, and converge teams on the right fix.

What we need to see:

• MS or PHD in EE or equivalent experience.

• Strong software engineering background with 8+ years significant experience designing large-scale infrastructure, framework architecture, or developer platforms.

• Strong proficiency in Python and at least one static language (C, C++, C#, Java, Scala, etc).

• Hands-on experience in AI/ML and data analysis, preferably with exposure to large-scale datasets.

• Strong EE fundamentals, including computer architecture, high-speed interfaces, timing, power basics, and a solid understanding of firmware/driver structures and hardware interaction.

• Excellent problem-solving, communication, and collaboration skills.

• Ability to break down ambiguous technical problems, explain failure modes and edge cases, and make strong tradeoff decisions under schedule, coverage, quality, and performance constraints.

• Track record of independently driving complex, cross-functional work to closure with clear ownership and strong collaboration.

Ways to stand out from the crowd:

• Hands-on experience with silicon bring-up, characterization, or lab debug using standard tools (e.g., oscilloscopes, multimeters, logic analyzers).

• Experience on building production AI workflow systems for engineering or infrastructure use cases, not just prototypes.

• Strong debugging instincts across distributed systems, automation pipelines, and HW/SW interactions, and can explain your hypothesis tree, measurement plan, tradeoffs, and final decision points.

• Track record of AI Experience to accelerate coding, analysis, validation, or triage with strong engineering judgment and validation discipline