Roles/Responsibilities:

1. Defines and drives the organization's AI strategy, aligning innovation priorities with enterprise goals, governance standards, and technology infrastructure needs.
2. Serves as the primary contact for AI initiatives across the organization, advising leadership on capabilities, risks, compliance, opportunities, and platform selection (e.g., Snowflake, AWS, Microsoft).
3. Identifies, evaluates, and prioritizes AI opportunities from ideation through scalable execution, ensuring business value and measurable outcomes.
4. Defines and monitors AI-specific KPIs to track impact, solution reliability, adoption, and ROI, in line with business outcomes.
5. Stays at the forefront of AI trends and advancements, integrating relevant technologies, frameworks, industry standards, and best practices into the enterprise AI strategy.
6. Designs and guides implementation of enterprise-grade AI and GenAI architecture and solutions, working with technical teams to assess infrastructure needs, tool selection, and implementation paths (e.g., RAG, foundational model integration, ML pipelines).
7. Leads the evaluation and adoption of AI tools and platforms (e.g., Azure ML, Dataiku, Snowflake), balancing innovation with governance, scalability, and compliance requirements.
8. Establishes and enforces AI governance frameworks ensuring ethical, transparent, and compliant AI usage across all enterprise initiatives.
9. Establishes MLOps best practices across the organization and develop reusable components and patterns for ingestion, feature engineering, training, deployment, and monitoring, ensuring model traceability and reproducibility.
10. Develops and deliver AI solutions and frameworks, guiding internal teams through proof of concept to production, while championing reuse, model traceability, and operational excellence.
11. Partners with internal teams to drive 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.
12. Performs other related duties as assigned.

Mandatory Skills:

1. Bachelor's degree in Artificial Intelligence, Computer Science, Data Science, or a related field.
2. Eight (8) or more years of experience in applied Data Science, with leadership in ML/AI strategy, solution delivery, and cross-functional program execution.
3. Proven experience in leading cross-functional AI initiatives and developing governance structures.
4. Advanced understanding of machine learning, deep learning, and generative AI, including LLMs, transformers, RAG architectures, and model fine-tuning.
5. Ability to lead AI efforts through strategic direction, platform/tool identification, and collaboration with technical experts.
6. Ability to move AI models from experimentation to production, with experience in model evaluation, explainability, and continuous improvement.
7. Experience designing and implementing MLOps pipelines for training, validation, deployment, monitoring, and retraining.
8. Skill with tools such as Snowflake AI/ML, Azure ML, and Dataiku.
9. Experience working with cloud-based infrastructure.
10. Ability to translate complex AI concepts into business value and communicate technical findings to non-technical audiences.
11. Experience in identifying AI opportunities that align with strategic objectives, quantify ROI, and prioritize initiatives based on impact and feasibility.
12. Ability to work effectively with cross-functional teams including engineering, analytics, governance, product development, and business stakeholders.
13. Knowledge of responsible AI principles, including fairness, bias mitigation, transparency, and regulatory compliance.
14. Knowledge of AI governance frameworks, model risk management practices, and ability to align AI development with compliance and security policies.
15. Experience partnering with data governance or compliance teams to ensure ethical use of AI within an enterprise setting.
16. Experience mentoring and guiding engineers, or analytics teams through AI solution design and implementation.
17. Ability to effectively influence without authority and foster a culture of innovation and responsible experimentation.
18. Skill with managing multiple initiatives simultaneously while maintaining high standards of technical rigor and strategic alignment.

Desirable Skills:

1. Master's or PhD in Artificial Intelligence, Computer Science, Data Science, or a related field.
2. Advanced certifications in AI/ML (e.g., AWS Certified Machine Learning, TensorFlow Developer, Microsoft Azure AI Engineer, etc.).
3. Experience leading or contributing to the creation of enterprise AI/ML platforms, AI centers of excellence, or federated AI governance models.
4. Expertise in Snowflake architecture, including best practices for AI/ML model integration and optimization.
5. Familiarity with programming in Python and AI/ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn, Hugging Face).
6. Experience delivering AI models in diverse domains (e.g., forecasting, NLP, recommendation systems, computer vision) with a strong governance lens