Principal AI Security Architect

About the role

This role defines architectures for scalable and secure high-performance AI accelerators used by datacenter customers. The position operates at the intersection of hardware, software, and security across the full computing stack.

Data roles turn raw information into decisions. Analysts query databases and build dashboards. Data scientists build models that predict outcomes. Data engineers build the pipelines that move and store data. All three work closely with business teams and need a mix of statistics, coding, and communication. Nearly every modern company runs on data teams, from startups to banks. A strong portfolio of past analyses matters more than degrees in many hiring decisions.

Key facts

What you'll do

Architectural innovations shape next generation inference and network accelerator capabilities to serve datacenter workloads.

Design decisions draw on ongoing research in machine learning, system architecture, and security to define robust computing foundations.

System requirements from customers transform into coherent computing system architectures that meet reliability and safety expectations.

Implementation and verification teams realize design specifications into hardware and software components across the stack.

Requirements

Master of Science in Electrical Engineering or equivalent with 15+ years of experience or a Doctor of Philosophy with 10+ years of applicable experience is mandatory.

Demonstrated experience spans computer architecture, secure computing, distributed systems, datacenter reliability and manageability, and ML fundamentals to address complex tradeoffs.

Fluency in C/C++ or Python enables rapid prototyping of new concepts for experimentation and early validation.

Familiarity with RTL represents a beneficial skill that supports hardware-software alignment.

A record of patents and publications in top-tier architecture, security, or machine learning venues demonstrates innovation depth.

Collaboration with design, verification, and software partner teams drives coherent and reliable outcomes.

Self-motivation guides work as a collaborative team member who takes initiative on challenging problems.

Practical notes

Hybrid work is supported in Santa Clara, CA, or fully Remote.

Typical interview steps

Data interviews commonly include a SQL or coding exercise, a statistics question, and a case study. Candidates may be asked to design a metric, interpret an experiment, or build a small model. Some companies give a take-home analysis. Expect questions about past projects and the business impact of your work. Interviewers often evaluate how you communicate uncertainty and business impact, not only the math. Bringing a clean write-up of a past analysis to the interview is well received.

Good to know

AI security architects focus on protecting models, data, and infrastructure across the hardware and software stack.

Secure computing practices address threats across the memory hierarchy, communication links, and execution pipelines.

Computer architecture designs balance throughput, latency, power, and reliability for datacenter workloads.

Hardware software co-design aligns accelerator features with software frameworks and runtime systems.

System reliability and manageability features keep large scale deployments stable and observable.

Questions to ask

Worth asking in any interview: how the team measures success, who the role works with daily, what the onboarding looks like, and what the company is trying to achieve this year. Asking what past hires did well is a strong final question. Keep the list short and pick the questions that matter most to you.

Career growth

Data careers grow toward senior analyst, staff data scientist, or data engineering lead. Many professionals specialize in machine learning, analytics, or infrastructure. Cross-functional work with product and engineering teams becomes more important at senior levels. The field changes quickly, so continuous learning is part of the job. Professionals who can translate numbers into decisions tend to advance fastest.