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Embedded Ai Jobs in Arizona (NOW HIRING)

... and embedded in delivery practices. • Shape and improve architecture governance processes ... AI solution delivery. • Mentor architects, engineers, and data scientists on design practices ...

Ensure Committee decisions are socialized across teams and embedded in delivery practices. People ... Leveraging AI to Improve Cybersecurity * Identify opportunities where AI can enhance cybersecurity ...

Ensure Committee decisions are socialized across teams and embedded in delivery practices. People ... Leveraging AI to Improve Cybersecurity * Identify opportunities where AI can enhance cybersecurity ...

You'll have the opportunity to work on our next generation of embedded hardware, including electronic speed controllers (ESCs), gimbal controllers, UAV power distribution boards, and advanced AI ...

You'll have the opportunity to work on our next generation of embedded hardware, including electronic speed controllers (ESCs), gimbal controllers, UAV power distribution boards, and advanced AI ...

You'll have the opportunity to work on our next generation of embedded hardware, including electronic speed controllers (ESCs), gimbal controllers, UAV power distribution boards, and advanced AI ...

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Embedded Ai information

What are the key skills and qualifications needed to thrive in the embedded AI position, and why are they important?

Success as an Embedded AI professional requires expertise in embedded systems, proficiency in C/C++, Python, and AI algorithms, often backed by a degree in computer engineering or related fields. Familiarity with real-time operating systems (RTOS), development tools like MATLAB, and frameworks such as TensorFlow Lite or ONNX is common, and certifications in embedded or machine learning domains are beneficial. Strong problem-solving skills, attention to detail, and the ability to communicate complex technical concepts clearly are crucial soft skills. These abilities ensure reliable integration of AI models into hardware, fostering innovation and seamless collaboration with multidisciplinary teams.

What is an embedded AI?

An Embedded AI job involves developing and optimizing artificial intelligence models to run efficiently on edge devices with limited computing power, such as IoT devices, autonomous systems, and smart sensors. Professionals in this field work on integrating AI algorithms with embedded systems, ensuring real-time performance, low power consumption, and efficient resource utilization. They collaborate with hardware and software engineers to deploy machine learning models on microcontrollers, FPGAs, or specialized AI accelerators.

What are some common challenges faced by embedded AI professionals in their day-to-day work?

Embedded AI professionals often encounter challenges such as optimizing AI algorithms to run efficiently within the memory and processing constraints of embedded hardware. They must also ensure reliable real-time performance and work to address issues with power consumption and system integration. Collaboration with hardware engineers, data scientists, and software developers is essential to align AI models with platform capabilities. Overcoming these challenges requires continuous learning and adaptability, but the role offers significant opportunities to make impactful contributions to emerging technologies.

What are the most commonly searched types of Embedded Ai jobs in Arizona? The most popular types of Embedded Ai jobs in Arizona are:
What cities in Arizona are hiring for Embedded Ai jobs? Cities in Arizona with the most Embedded Ai job openings:
Infographic showing various Embedded Ai job openings in Arizona as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Cybersecurity AI Architect

onsemi

Scottsdale, AZ • On-site

Full-time

Re-posted 25 days ago


Onsemi rating

8.3

Company rating: 8.3 out of 10

Based on 20 frontline employees who took The Breakroom Quiz


Job description

Job Summary:
onsemi is driving disruptive innovations to help build a better future, and they are seeking a Cybersecurity AI Architect to tackle complex problems that blend AI, cloud, data, and cybersecurity. The role focuses on enabling teams to deliver AI-enabled technical solutions and advising on secure architectures that align technology and business outcomes.
Responsibilities:
• Partner with Business, IT, Engineering, and Data Science teams to co-design secure, scalable, and AI technical solutions.
• Facilitate collaborative architecture sessions, workshops, and design sessions to guide teams toward well-informed architectural decisions.
• Translate architectural considerations into clear execution steps that empower delivery teams and accelerate solution deployment.
• Help teams navigate ambiguity by clarifying tradeoffs across technology, people, and process dimensions.
• Serve as a trusted advisor by preparing architectural evaluations, risk assessments, and decision frameworks for Committee review.
• Contribute to enterprise AI guardrails, patterns, and reference architectures that ensure safe and responsible AI adoption.
• Support Committee decision-making through clear communication of risks, options, and implications across stakeholders.
• Ensure Committee decisions are socialized across teams and embedded in delivery practices.
• Shape and improve architecture governance processes including intake, review, and lifecycle management.
• Develop templates, checklists, and reusable patterns that simplify responsible AI solution delivery.
• Mentor architects, engineers, and data scientists on design practices, governance expectations, and communication skills.
• Promote collaboration, transparency, and accountability across cross-functional teams.
• Identify opportunities where AI can enhance cybersecurity automation, anomaly detection, and threat intelligence.
• Provide guidance on safe integration of AI into security workflows, addressing risks such as data leakage and unsafe automation.
• Develop secure patterns for connecting AI systems with SIEM, SOAR, EDR, and XDR platforms.
Qualifications:
Required:
• 8+ years in technology/cybersecurity roles with at least 4 years in architecture.
• Experience co-developing solution designs with Business and IT partners.
• Strong facilitation and communication skills to lead cross-functional collaboration.
• Experience designing and implementing AI-enabled architectures and creating architecture artifacts.
• Understanding of AI/ML concepts and responsible AI practices.
• Knowledge of scripting languages such as Python or PowerShell, and experience with automation tools (e.g., Terraform)
• Understanding of security frameworks and standards including NIST, SOC, and ISO 27001
• Strong familiarity with AI regulations, AI security frameworks, and emerging AI assurance standards
• Experience implementing or architecting AI, ML, or automation technologies within IAM or broader cybersecurity domains
Preferred:
• Certifications such as CISSP, CCSP, SABSA, CRISC.
• Experience with AI governance frameworks and architecture committees.
• Background in technology strategy, architecture governance, or security research.
• Education: BS/MS preferred
Company:
onsemi (Nasdaq: ON) is driving disruptive innovations to help build a better future. Founded in 1999, the company is headquartered in Scottsdale, USA, with a team of 10001+ employees. The company is currently Late Stage.

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