Senior Director, Software Engineering – AI, Ontology

• Define and own end-to-end software architecture for AI/ML-enabled platforms, emphasizing ontologies, semantic models, and knowledge representation
• Lead scalable, production-grade AI/ML systems, including data pipelines, model lifecycle management, and inference services
• Drive development and adoption of enterprise ontologies and domain models for interoperability, reasoning, explainability, and data reuse
• Ensure architectural alignment across cloud, edge, and on-premises deployments
• Establish engineering best practices for model governance, explainable AI, data quality, security, and compliance
• Partner with product, data science, and business leaders to identify high-value AI/ML use cases and create engineering roadmaps
• Guide teams on model selection, training strategies, feature engineering, and MLOps
• Evaluate and integrate emerging AI technologies, frameworks, and tools
• Advise senior leaders on complex architectural and AI concepts
• Influence enterprise standards and long-term AI, data, and software engineering strategy
• Collaborate with global engineering, security, legal, and compliance teams on responsible AI deployment
• Report directly to the VP Chief Technology Officer – Forge & AI
• Mentor senior architects and influence executive stakeholders

Requirements

• 10+ years of progressive software engineering experience
• Experience with 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
• Combination of hands-on technical depth and strategic leadership experience
• Must be a U.S. Person: U.S. citizen, U.S. permanent resident, protected status under asylum or refugee status, or able to obtain export authorization
• Bachelor’s and advanced degrees in Computer Science, Engineering, AI, Data Science, or a related field are valued
• 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
• Ability to lead senior technical talent and influence across organizational boundaries

Core Competencies

Demonstrates expertise in defining and owning software architecture for AI/ML platforms, with a strong focus on ontologies, semantic models, and model governance. Proven ability to lead scalable AI/ML systems and collaborate with cross-functional teams to drive high-value use cases and engineering roadmaps.

Highest-signal resume keywords

• AI/ML System Development
• Ontology Design
• MLOps Platforms
• Cloud-Native Architectures
• Model Governance

ATS Optimization Keywords

Hard Skills

• Software Engineering
• Semantic Modeling
• Knowledge Representation
• Data Pipeline Management
• Model Lifecycle Management
• Feature Engineering
• Explainable AI
• Data Quality Assurance
• Security Compliance
• Distributed Systems

Soft Skills

• Strategic Leadership
• Mentoring
• Collaboration
• Influencing Stakeholders
• Cross-Organizational Communication

Industry Keywords

• Enterprise Ontologies
• Regulatory Compliance
• Ethical AI
• Industrial Domains
• Data Reuse

Tools & Technologies

• AI Frameworks
• MLOps Tools
• Cloud Platforms
• Data Science Tools
• Knowledge Graphs