AI Integration Engineer

Littelfuse (NASDAQ: LFUS) is a diversified industrial technology manufacturing company shaping solutions for the safe and efficient transfer of electrical energy. Headquartered in Chicago, Illinois, USA, we serve customers across industrial, transportation, and electronics markets worldwide. With approximately 16,000 employees we design and manufacture innovative technologies that support electrification, energy efficiency, and advanced automation. Our global reach is matched by a culture that empowers innovation and long-term growth. Guided by our principles We Care, We Succeed With Our Customers, and We Own the Outcome, we work collaboratively, think boldly, and deliver solutions that move industries forward.

Littelfuse is seeking a highly motivated person to join the Industrial Circuit Protection (ICP) Engineering team as an AI Integration Engineer. Reporting to the Sr. Manager of Global ICP Engineering, the AI Integration Engineer will serve as the technical expert and implementation lead for applying artificial intelligence across our engineering team’s tools, processes, and data. The individual will identify where AI can deliver the greatest value, recommend practical solutions, and then build, deploy, and drive adoption of approved solutions so engineers can work faster and with greater confidence in their data. The candidate should be an experienced engineer who understands how products are developed and launched, and who has a demonstrated passion for using AI to improve workflow, efficiency, and data reliability. Success in this role will be measured by improved system quality and faster speed to market for new products.

The AI Integration Engineer will support multiple engineering functions including New Product Development and Introduction, Application Engineering, Project Management, and Sustaining Engineering. The position will serve a critical role for our growing business, partnering with engineers across our global ICP team. The role will propose AI opportunities for the engineering roadmap, evaluate and recommend the infrastructure and tools needed to support them, and help implement approved processes that enable responsible and consistent use of AI within the engineering teams. Strategic direction, priorities, and final technology decisions remain with ICP engineering leadership.

About the Job:

• Partner with engineering teams to identify opportunities where AI can improve workflow, efficiency, and decision making
• Support development of the AI roadmap by proposing use cases with clear business value, KPIs, and implementation plans, and lead execution of the approved roadmap
• Design, build, and deploy approved AI-enabled tools and automations that integrate with existing engineering systems
• Contribute technical expertise to the engineering data strategy and carry out improvements to the quality, structure, and reliability of engineering data (test results, design records, specifications) so it can be used effectively by AI and analytics tools
• Apply AI and machine learning to accelerate simulation, reliability analysis, test data review, and design validation
• Leverage AI to streamline project management, documentation, reporting, and knowledge sharing across engineering
• Support sustaining engineering with AI-assisted root cause analysis, change management, and continuous improvement
• Evaluate and pilot AI platforms and tools and recommend options for approval, working with IT to support data security, governance, compliance, and responsible-use processes
• Recommend AI best practices, implement approved standards, and train and coach engineers on AI tools to drive adoption
• Lead delivery and adoption of approved AI initiatives, and measure and communicate their impact on system quality, engineering productivity, and speed to market for new products

Requirements:

• Bachelor’s degree in Electrical, Mechanical, or Industrial Engineering, Computer Science, or similar discipline
• 5–10 years of experience in a product or process development engineering role
• Demonstrated passion for, and track record of, applying AI to improve engineering workflow, efficiency, or data quality
• Practical experience with generative AI and large language model tools incorporating into business workflows
• Proficiency in Python or a similar language for data analysis, automation, and tool development
• Understanding of the product development lifecycle, including design, validation, and launch of new products
• Experience working with engineering data from test, simulation, reliability, or manufacturing sources
• Flexible and willing to work with multiple functional groups within the company
• Highly capable problem solver with strong analytical skills and high attention to detail
• Robust communication skills and fluent in English (written and verbal), with the ability to explain technical concepts
• Self-motivated and able to work effectively in a fast-paced, international organization
• Proficient in Microsoft Office Products
• Willing to travel occasionally to Littelfuse engineering sites

Preferred:

• Experience with machine learning frameworks, data pipelines, cloud AI platforms, or low-code automation tools, ideally applied to electrical products, circuit protection, or reliability engineering
• Master’s degree in Engineering, Data Science, Computer Science, or similar discipline

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Artificial intelligence (AI) tools may be used in some portions of the candidate review process for this position, however, all final employment decisions will be made by a person.

Salary Range:

$88,500 - $137,100The salary offered will vary depending on your location, job-related skills, knowledge, and experience.

At Littelfuse, we support employee growth and development. Guided by our culture principles, our teams work together to deliver value for customers and make a positive impact in the communities where we operate. We are an equal opportunity employer committed to fostering an inclusive workplace where everyone has the opportunity to grow and contribute. We offer competitive compensation and benefits, performance-based incentives, flexible work arrangements, and development opportunities.