Senior Director of Software Engineering – AI/ML & Ontology

Honeywell•Atlanta, GA

10h•Hybrid

About The Position

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.

Requirements

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.

Nice To Haves

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

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