Sr Director Software Engineering, Ontology & AI

Responsibilities

• 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.
• 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.
• Lead and develop a small, elite team of senior architects, fostering a culture of technical excellence, accountability, and continuous learning.
• Act as a mentor and technical coach, raising the bar for architectural thinking, engineering rigor, and AI fluency.
• 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.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, AI, Data Science, or related field.
• 12 plus years of progressive software engineering experience, including senior leadership roles.
• Demonstrated, hands-on experience delivering AI/ML-powered production systems at scale.
• Deep expertise in ontology design, semantic modeling, knowledge graphs, or domain-driven data models.
• Strong background in cloud-native architectures, distributed systems, and modern software engineering practices.
• Proven ability to lead senior technical talent and influence across organizational boundaries.

Preferred Qualifications

• PhD or advanced research background in AI, ML, or knowledge representation.
• 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.

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.

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About Us

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.