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As Senior Director Software Engineering - Artificial Intelligence (AI) & Ontology at Honeywell Technologies, you will be responsible for designing and scaling next-generation intelligent platforms. This role sits at the intersection of advanced engineering, data/AI strategy, and enterprise architecture, translating complex business and customer challenges into robust, scalable, and explainable AI-enabled solutions. The Senior Director will be both strategic and hands-on, setting technical direction while mentoring senior architects and influencing executive stakeholders.

You will report directly to the VP Chief Technology Officer - Forge & AI and will work out of the Atlanta, GA office on a hybrid work schedule.

Honeywell helps organizations solve the world's most complex challenges in automation, the future of aviation and energy transition. As a trusted partner, we provide actionable solutions and innovation through our Aerospace Technologies, Building Automation, Energy and Sustainability Solutions, and Industrial Automation business segments - powered by our Honeywell Forge software - that help make the world smarter, safer and more sustainable.

YOU MUST HAVE

• 10+ years of progressive software engineering experience, including cloud-native architectures, distributed systems, and modern software engineering practices
• Hands-on experience with ontology design, semantic modeling, knowledge graphs, or domain-driven data models
• Demonstrated success delivering AI/ML-powered production systems at scale
• Blend of hands-on technical depth and strategic leadership experience

US PERSON REQUIREMENTS

Due to compliance with U.S. export control laws and regulations, candidate must be a U.S. Person, which is defined as, a U.S. citizen, a U.S. permanent resident, or have protected status in the U.S. under asylum or refugee status or have the ability to obtain an export authorization.

WE VALUE

• Bachelor's and advanced degrees in Computer Science, Engineering, AI, Data Science, or related field
• Strong background in cloud-native architectures, distributed systems, and modern software engineering practices
• Experience with MLOps platforms, model governance, and AI lifecycle management.
• Familiarity with explainable AI, ethical AI, and regulatory considerations in enterprise environments.
• Prior experience in industrial, enterprise, or highly regulated domains.
• Proven ability to lead senior technical talent and influence across organizational boundaries

BENEFITS OF WORKING FOR HONEYWELL TECHNOLGIES

In addition to a competitive salary, leading-edge work, and developing solutions side-by-side with dedicated experts in their fields, Honeywell Technologies employees are eligible for a comprehensive benefits package. This package includes employer subsidized Medical, Dental, Vision, and Life Insurance; Short-Term and Long-Term Disability; 401(k) match, Flexible Spending Accounts, Health Savings Accounts, EAP, and Educational Assistance; Parental Leave, Paid Time Off (for vacation, personal business, sick time, and parental leave), and 12 Paid Holidays. For more information, Click Here.

Honeywell Technologies is an equal opportunity employer. Qualified applicants will be considered without regard to age, race, creed, color, national origin, ancestry, marital status, affectional or sexual orientation, gender identity or expression, disability, nationality, sex, religion, or veteran status. Learn more about inclusion and engagement:  Click Here 

KEY RESPONSIBILITIES 

Technical & Architectural Leadership

• Define and own the end-to-end software architecture for AI/ML-enabled platforms, emphasizing ontologies, semantic models, and knowledge representation.
• Lead the design and implementation of scalable, production-grade AI/ML systems, including data pipelines, model lifecycle management, and inference services.
• Drive the development and adoption of enterprise ontologies and domain models to enable interoperability, reasoning, explainability, and data reuse across platforms.
• Ensure architectural alignment across cloud, edge, and on-prem deployments.
• Establish engineering best practices around model governance, explainable AI (XAI), data quality, security, and compliance.

AI/ML Strategy & Execution

• Partner with product, data science, and business leaders to identify high-value AI/ML use cases and translate them into executable engineering roadmaps.
• Guide teams on model selection, training strategies, feature engineering, and MLOps, ensuring solutions are robust, ethical, and scalable.
• Evaluate and integrate emerging AI technologies, frameworks, and tools with a pragmatic, value-driven mindset.

Stakeholder & Enterprise Influence

• Serve as a trusted technical advisor to senior leaders, clearly communicating complex architectural and AI concepts to both technical and non-technical audiences.
• Influence enterprise standards and long-term technology strategy related to AI, data, and software engineering.
• Collaborate closely with global engineering, security, legal, and compliance teams to ensure responsible AI deployment.