Senior Director of Software Engineering – AI​/ML & Ontology

Senior Director of Software Engineering – AI/ML & Ontology

Join to apply for the Senior Director of Software Engineering – AI/ML & Ontology role at Honeywell

We are seeking a Senior Director of Software Engineering with deep expertise in Artificial Intelligence (AI), Machine Learning (ML), and Ontology-driven systems 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.

• 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.
• People Leadership & Team Development
  • 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.
• 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.

• Required Qualifications
  • Bachelor’s or Master’s degree in Computer Science, Engineering, AI, Data Science, or related field.
  • 12+ 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.

• AI/ML platforms are scalable, explainable, and grounded in strong ontological foundations.
• Architects are aligned, empowered, and operating as trusted technical leaders across the organization.
• Complex data and AI challenges are translated into clear, actionable architectures that deliver real business value.
• The organization’s AI capabilities mature in a responsible, sustainable, and enterprise‑ready way.

In addition to a competitive salary, leading‑edge work, and developing solutions side‑by‑side…