Dir, AI/ML Engineering
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In this role you will lead the strategy and delivery of an enterprise context layer to support generative AI and agentic workflows. You will build AI-ready data foundations, including semantic models, ontologies, and knowledge graphs, enabling trusted, secure, and understandable AI agents. You’ll guide cross-functional teams to establish standards for context engineering, data quality, and governance, while shaping the broader enterprise AI roadmap. This position offers remote work from anywhere in the U.S. and opportunities to drive scalable, impactful AI solutions at scale.
Compensation / Benefits
- remote work flexiblity
- comprehensive benefits package
- equity stock purchase
- 401k contribution
- incentive and recognition programs
- career development opportunities
Responsibilities
- Lead and direct AI/ML engineering teams to design and deliver enterprise-scale ML systems and intelligent platforms
- Partner with senior tech, data, analytics, product, and business leaders to embed semantic and contextual foundations into the enterprise AI strategy
- Define and own the enterprise strategy and roadmap for AI-ready data, semantic architecture, knowledge graphs, and contextual data platforms
- Establish an architectural vision for the context layer to support generative AI, intelligent search, and agentic workflows
- Identify semantic, contextual, and data-quality capabilities needed for AI agents to understand business entities, relationships, processes, and constraints
- Translate AI priorities into a sequenced portfolio of foundational data, metadata, ontology, and knowledge-graph capabilities
- Utilize enterprise-approved AI tools to streamline workflows and drive continuous improvement
- Evaluate emerging trends to inform solution design, platform scalability, and innovation
- Mentor and cultivate technical leaders to ensure ongoing growth and team capability
Key requirements
- 10+ years in AI/ML engineering, data engineering, data architecture, knowledge engineering, or semantic technologies
- 5+ years leading technical teams and translating business needs into platform capabilities
- 3+ years designing semantic xhuatnn models, ontologies, taxonomies, or knowledge graphs
- 3+ years integrating structured and unstructured data into AI-ready platforms
- Understanding of data products, metadata, lineage, data quality, governance, and access controls
- Understanding of generative AI, LLMs, retrieval-augmented generation, vector search, and agentic AI workflows
- strong stakeholder influence
- leadership and mentorship
- strategic thinking and roadmap execution
- semantic models, ontologies, taxonomies, knowledge graphs
- metadata, data quality, governance, access controls
- generative AI, large language models, retrieval-augmented generation
Remote working/work at home options are available for this role.
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