Sr Director Software Engineering, Ontology & AI

Posted Yesterday
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Atlanta, GA, USA
Hybrid
Senior level
Aerospace
The Role
Lead architecture and delivery of ontology-driven, production-grade AI/ML platforms. Define enterprise ontologies, semantic models, and scalable data/model pipelines. Drive MLOps, model governance, XAI, cloud/edge/on-prem architectures. Mentor senior architects, influence executives, and ensure responsible AI adoption across the enterprise.
Summary Generated by Built In

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.

Responsibilities

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.

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.
Qualifications

Required 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.
 

What Success Looks Like

  • 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.

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.

#Li-Hybrid

In addition to a competitive salary, leading-edge work, and developing solutions side-by-side with dedicated experts in their fields, Honeywell 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 visit: Benefits at Honeywell

The application period for the job is estimated to be 40 days from the job posting date; however, this may be shortened or extended depending on business needs and the availability of qualified candidates.


About UsHoneywell 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.

Skills Required

  • 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
  • Hands-on experience delivering AI/ML-powered production systems at scale
  • Deep expertise in ontology design, semantic modeling, and knowledge graphs
  • Strong background in cloud-native architectures and distributed systems
  • Experience with model lifecycle management, MLOps, and production inference services
  • Establishing engineering best practices around model governance, explainable AI, data quality, security, and compliance
  • Proven ability to lead senior technical talent and influence across organizational boundaries
  • Must be a U.S. Person (U.S. citizen, permanent resident, refugee/asylee, or able to obtain export authorization)
  • 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
  • Prior experience in industrial, enterprise, or highly regulated domains
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The Company
Mississauga, Ontario
10,000 Employees
Year Founded: 1914

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