Explainable Ai Jobs in Georgia (NOW HIRING)

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.

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.

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.