Director of Applied AI

Director of Applied AI

Department: Data and Analytics

The Team

We are seeking a Director of Applied AI to join a Data and Analytics team within IT. The team advances enterprise insights, decision intelligence, and AI-enabled value creation across the organization.

The Director develops and operationalizes machine learning models, generative AI systems, Agentic AI solutions, and autonomous decisioning capabilities that drive measurable business outcomes. Day to day, the Director identifies high-value opportunities, designs experiments, builds production-grade models and agents, and ensures continuous monitoring and safe operation.

This role partners with Data Engineering, Data Product and Adoption, Data Strategy and Governance, and Technology teams to deliver scalable, high-impact AI and Agentic AI solutions.

What You Can Offer Us (Job Responsibilities)

• Lead the Applied AI function, including the development of machine learning, optimization, generative AI, and Agentic AI systems that perform multi-step reasoning, autonomous workflows, and decision support.
• Oversee model and agent lifecycle development, including methodology design, feature engineering, validation, safety constraints, agent orchestration, and performance monitoring.
• Partner with Data Engineering to enable MLOps, AgentOps, deployment, observability, retraining, and production reliability.
• Collaborate with Data Product and Adoption teams to translate models and agents into user-facing products that drive adoption and measurable value realization.
• Establish and enforce enterprise standards for documentation, scientific rigor, reproducibility, Responsible AI, and safe Agentic AI practices, including human-in-the-loop oversight.
• Other duties as assigned.

As a Director, you are responsible for the recruitment, performance management, and career development of Data Scientists, ML Engineers, and AI Engineers. You will cultivate a collaborative team dynamic that enables the organization to meet its business objectives.

What You Need to Succeed (Qualifications, Experience, and Education)

Education:

• Bachelor’s degree in Data Science, Computer Science, Engineering, Mathematics, Operations Research, or a related field required.
• Advanced degree (Master’s or PhD) preferred.

Experience:

• A minimum of 10 years of data science, machine learning, advanced analytics, or applied AI experience required, with 5 or more years leading technical AI teams strongly preferred.
• Success developing and deploying production-grade ML, generative AI, optimization models, or Agentic AI systems in complex or asset-intensive environments.
• Experience with experimental design, causal inference, predictive modeling, reinforcement learning, and autonomous decisioning systems.

Technical and Professional Requirements:

• Strong expertise in Python, ML frameworks, LLMs, vector search, embeddings, and agent-orchestration frameworks.
• Experience with MLOps, AgentOps, model and agent registries, feature stores, monitoring, and AI safety tooling.
• Strong business acumen with the ability to quantify impact, communicate model and agent behavior, and influence senior stakeholders.
• Familiarity with Responsible AI practices for autonomy, including safety constraints, guardrails, alignment testing, and human-in-the-loop design.
• Experience in global, matrixed environments preferred.
• Approximately 20%–30% travel may be required.

Standard Qualifications

• Strong organization, planning, and project management skills; ability to prioritize tasks for yourself and a team.
• Ability to work with different functional groups and levels of employees to effectively and professionally achieve results.
• Strong leadership skills with ability to drive and motivate a team to achieve results.

Equal Opportunity Statement

We are proud to be an equal opportunity employer and will not discriminate against an applicant or employee based on age, sex, sexual orientation, gender identity, race, color, creed, religion, national origin or ancestry, citizenship, marital status, familial status, disability, military or veteran status, genetic information, pregnancy, or any other characteristic protected under applicable law.