Principal Engineering AI Solution Architect #1064565

The Job:  
As Principal Engineering AI Solution Architect in Townson, Maryland, you'll be part of our Electronics & Electrical team working as a hybrid employee. The  Principal Engineering AI Solution Architect to serve as a strategic individual contributor shaping the vision, development, and implementation of AI initiatives within Engineering. This role sits within the Engineering organization and is intended first and foremost for an experienced engineer who understands the realities of physical product development and has subsequently applied AI to improve engineering outcomes. This is not a pure IT or software AI role. We are looking for someone who has lived the product development process, understands the pain points engineers face across design, controls, validation, and release, and can apply AI in practical, high-value ways that make the Engineering Excellence team more effective.
 
You'll get to:  

• Architect AI-driven solutions embedded in the product engineering lifecycle: CAD/PLM data, embedded firmware and controls development, and test/validation workflows. Apply AI/ML to mechatronic systems and embedded controls e.g., predictive diagnostics, sensor fusion, and motor/battery control optimization for power tool platforms.
• Develop digital twins and physics-informed / surrogate models that connect CAE and simulation data with AI to accelerate design iteration.
• Partner with product engineering, controls/firmware teams, and manufacturing engineering to define solution requirements and technical specifications.
• Build AI capabilities for engineering shared services: automated workflows, design-for-reliability analytics, and simulation-assisted design.
• Collaborate with cross-functional teams (engineering, product management, data science, and IT) to define solution requirements and technical specifications.
• Coordinate and oversea the end-to-end implementation of AI projects for product engineering, from ideation and prototyping to deployment and monitoring.
• Evaluate and select appropriate AI technologies, frameworks, and tools appropriate to embedded and engineering-domain constraints..
• Guide and mentor engineering teams on AI/ML model integration, data pipelines, and cloud deployment strategies.
• Develop and maintain AI roadmaps for engineering.
• Ensure compliance with data privacy, security, and regulatory requirements in all AI solutions.
• Stay updated with the latest AI trends, research, and technologies to drive innovation within the organization.
• Participate in client meetings, presentations, and technical workshops as a subject matter expert.

 
The Person:  
You love to learn and grow and be acknowledged for your valuable contributions. You're not intimidated by innovation. Wouldn't it be great if you could do your job and do a world of good? In fact, you embrace it. You also have: 

• Bachelor's or master's degree in engineering or computer science.
• 10+ years of experience in product engineering or embedded systems development, with 5+ years applying AI/ML to physical or engineered products and workflows — not solely IT systems.
• Proven track record of designing and deploying AI/ML solutions in production environments, including embedded or edge platforms.
• Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Strong understanding of machine learning algorithms, data engineering, and MLOps practices.

Preferred Qualifications

• Experience in power tools, industrial equipment, automotive, or similarly regulated hardware product industries.
• Background in mechatronics, robotics, or embedded AI.
• Certifications in cloud architecture or AI/ML (e.g., AWS Certified Machine Learning, Google Professional Machine Learning Engineer).
• Familiarity with edge computing and IoT integration.

Tools & Technologies

• Proficiency in programming languages such as Python, Java, or C++.
• Familiarity with CAD/CAE/PLM tools (e.g., SolidWorks, Ansys) or embedded toolchains
• (C/C++, RTOS, MATLAB/Simulink).
• Expertise in AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Experience with physics-informed ML, digital twins, or model-based design.
• Excellent problem-solving and analytical skills.
• Strong communication and presentation skills, with the ability to explain complex technical concepts to
• non-technical stakeholders.
• Experience with data modeling, ETL pipelines, and API design.
• Knowledge of DevOps practices and CI/CD pipelines.
• Ability to work independently and as part of a collaborative team.