Principal Engineering AI Solution Architect

Engineering AI Solution Architect — Hybrid

Location:

Towson, MD (Hybrid – onsite 3 days a week)

Principal Engineering AI Solution Architect responsible for shaping the vision, development, and implementation of AI initiatives across the engineering organization.

• Architect AI‑driven solutions for complex engineering problems, ensuring scalability, reliability, and security.
• Collaborate with cross‑functional teams (engineering, product management, data science, and IT) to define solution requirements and technical specifications.
• Coordinate and oversee the end‑to‑end implementation of AI projects, from ideation and prototyping to deployment and monitoring.
• Evaluate and select appropriate AI technologies, frameworks, and tools based on project needs.
• 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.

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
• 10+ years of experience with integrated HW‑SW product development, with 5+ years focused on AI/ML projects with engineering design applications.
• Proven track record applying AI/ML methods to drive transformational change in engineering.
• Proven track record of designing and deploying AI/ML solutions in production environments.
• Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Strong understanding of machine learning algorithms, data engineering, and MLOps practices.

• Proficiency in programming languages such as Python, Java, or C++.
• Expertise in AI/ML frameworks (Tensor Flow, PyTorch, Scikit‑learn).
• 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 Dev Ops practices and CI/CD pipelines.
• Ability to work independently and as part of a collaborative team.

• Certifications in cloud architecture or AI/ML (e.g., AWS Certified Machine Learning, Google Professional Machine Learning Engineer).
• Experience in manufacturing, automotive, or healthcare industries.
• Familiarity with edge computing and IoT integration.

Salary Range: $ – $ (annual full‑time).

• Medical, dental, life, vision, disability benefits.
• 401(k) with company match.
• Employee Stock Purchase Plan.
• Paid time off and tuition reimbursement.
• Employee discounts on Stanley Black & Decker tools and partner programs.

All qualified applicants to Stanley Black & Decker are considered for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran’s status or any other protected characteristic.