Principal AI Lead

DFW International Airport•Grapevine, TX

23h

About The Position

Under the direction of the Senior Enterprise Data Governance Manager, the Principal AI Lead serves as the strategic and technical authority on Artificial Intelligence (AI) across the organization. This role oversees the definition, governance, and implementation of the enterprise AI strategy, ensuring safe, ethical, and business-aligned AI adoption. The Principal AI Lead is the central point of contact for all AI-related initiatives, responsible for setting direction, evaluating new technologies, piloting use cases, building enterprise capabilities, and establishing controls to prevent unauthorized AI usage. The Principal AI Lead will work across legal, engineering, analytics, and transformation teams to ensure responsible AI innovation at scale.

Requirements

Eight (8) years of experience in applied data science, including leading ML/AI initiatives and mentoring teams in a production environment.
Master’s or PhD in Artificial Intelligence, Computer Science, Data Science, or a related field.
Proven experience in leading cross-functional AI initiatives and developing governance structures.
Advanced understanding of machine learning, deep learning, and generative AI, including LLMs, transformers, RAG architectures, and model fine-tuning.
Demonstrated ability to lead AI efforts through strategic direction, platform/tool identification, and collaboration with technical experts.
Demonstrated ability to move models from experimentation to production, with experience in model evaluation, explain ability, and continuous improvement.
Hands-on experience designing and implementing MLOps pipelines for training, validation, deployment, monitoring, and retraining.
Familiarity with tools such as Snowflake AI/ML, Azure ML, and Dataiku.
Experience working with cloud-based infrastructure.
Proven ability to translate complex AI concepts into business value and communicate technical findings to non-technical audiences.
Experience in identifying AI opportunities that align with strategic objectives, quantify ROI, and prioritize initiatives based on impact and feasibility.
Solid understanding of responsible AI principles, including fairness, bias mitigation, transparency, and explain ability.
Knowledge of AI governance frameworks, model risk management practices, and how to align AI development with compliance and security policies.
Experience partnering with data governance or compliance teams to ensure ethical use of AI within an enterprise setting.
Track record of mentoring and guiding engineers, or analytics teams through AI solution design and implementation.
Capable of influencing without authority, leading by expertise, and fostering a culture of innovation and responsible experimentation.
Skilled at managing multiple initiatives simultaneously while maintaining high standards of technical rigor and strategic alignment.

Nice To Haves

Advanced certifications in AI/ML (e.g., AWS Certified Machine Learning, TensorFlow Developer, Microsoft Azure AI Engineer, etc.).
Experience leading or contributing to the creation of enterprise AI/ML platforms, AI centers of excellence, or federated AI governance models.
Expertise in Snowflake architecture, including best practices for AI/ML model integration and optimization.
Familiarity with programming in Python and AI/ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn, Hugging Face).
Experience overseeing the development and deployment of AI models (e.g., demand forecasting, classification, recommendation systems, NLP, computer vision) with the ability to evaluate performance, ensure governance alignment, and translate outcomes into business value.
Comfortable working with cross-functional teams including engineering, analytics, governance, product, and business stakeholders

Responsibilities

Defines and drives the organization's AI vision and strategic roadmap, ensuring alignment with enterprise goals, governance and innovation priorities, and technology infrastructure needs.
Serves as the single point of contact for AI across the organization, guiding teams and leadership on capabilities, risks, compliance, opportunities, and recommending strategic platforms and partnerships (e.g., Snowflake, AWS, Microsoft).
Identifies, evaluates, and prioritizes AI use cases, supporting their advancement from ideation to scalable execution with measurable value.
Defines and track AI-specific KPIs to measure impact, reliability, and alignment of deployed solutions with business outcomes.
Stays at the forefront of AI trends, integrating emerging technologies, industry standards, and best practices into the enterprise AI strategy.
Architects enterprise-grade AI and GenAI solutions, works with technical teams to assess infrastructure needs, tool selection, and implementation paths (e.g., RAG, foundational model integration, ML pipelines).
Leads the selection and adoption of AI tools and platforms (e.g., Azure ML, Dataiku, Snowflake), balancing innovation with governance, scalability, and compliance requirements.
Establishes and enforce AI governance frameworks that ensures compliance with legal, ethical, and responsible AI usage across all enterprise initiatives.
Establishes MLOps best practices across the organization and develops reusable components and patterns for ingestion, feature engineering, training, deployment, and monitoring, ensuring model traceability and reproducibility.
Develops and delivers AI solutions and frameworks, guiding teams through proof of concept to production, while championing reuse, model traceability, and operational excellence.
Drives organizational readiness and literacy for AI, collaborating with HR, and business units to design training, raise awareness, and support the cultural shift needed for successful AI adoption.
Performs other related duties as assigned.