Director of Applied AI

A global organization is seeking a director of applied AI to lead the design, development, and operation of advanced artificial intelligence capabilities within a data and analytics function. This leadership role focuses on transforming data into enterprise value through production‑grade machine learning, generative AI, and agent‑based systems that support autonomous decisioning and multi‑step reasoning.

The director is responsible for identifying high‑impact use cases, guiding experimentation, and ensuring that AI systems are safely deployed, continuously monitored, and aligned with business priorities. This role works closely with data engineering, data product, adoption, and governance partners to deliver scalable, reliable, and responsible AI solutions.

Responsibilities

• Lead the applied AI function, overseeing the development of machine learning, optimization, generative AI, and agent‑based systems that support autonomous workflows and decision intelligence.
• Define and govern the full lifecycle of models and agents, including methodology selection, feature engineering, validation, orchestration, safety controls, and performance monitoring.
• Partner with data engineering teams to enable deployment, observability, retraining, reliability, and operational practices for models and agents.
• Collaborate with product and adoption teams to translate AI capabilities into user‑facing solutions that drive adoption and measurable business outcomes.
• Identify and prioritize high‑value opportunities for applied AI across enterprise use cases.
• Establish and enforce standards for documentation, scientific rigor, reproducibility, and responsible AI practices, including human‑in‑the‑loop oversight.
• Ensure safe operation of AI and agent‑based systems through monitoring, guardrails, and alignment practices.
• Recruit, manage, and develop a team of data scientists, machine learning engineers, and AI engineers.
• Build a collaborative, high‑performance team culture focused on delivery, accountability, and continuous improvement.
• Perform additional duties aligned with applied AI leadership as needed.

Required experience and skills

Education

• Bachelor’s degree in data science, computer science, engineering, mathematics, operations research, or a related field.
• Advanced degree preferred.

Experience

• Ten or more years of experience in data science, machine learning, advanced analytics, or applied AI.
• Five or more years of experience leading technical AI teams.
• Demonstrated success building and deploying production‑grade machine learning, generative AI, optimization, or agent‑based systems in complex environments.
• Experience with experimental design, causal inference, predictive modeling, reinforcement learning, and autonomous decisioning systems.
• Experience working in global or matrixed organizations.

Technical and professional skills

• Strong proficiency in Python and modern machine learning frameworks.
• Hands‑on experience with large language models, vector search, embeddings, and agent orchestration frameworks.
• Experience with operational practices such as model and agent registries, feature stores, monitoring, and AI safety tooling.
• Understanding of responsible AI for autonomous systems, including safety constraints, guardrails, alignment testing, and human‑in‑the‑loop design.
• Strong business acumen with the ability to quantify impact, explain model and agent behavior, and influence senior stakeholders.
• Willingness to travel approximately 20 to 30 percent.

Leadership and execution

• Strong organizational, planning, and project management skills.
• Ability to prioritize work for both individual contributors and teams.
• Proven ability to collaborate across functions and organizational levels.
• Demonstrated leadership skills with a track record of motivating teams and delivering results.

FAQ

1. What are the core responsibilities of a Director of Applied AI?
This role leads the strategy, development, and deployment of applied AI solutions across the organization. It involves identifying high-impact use cases, overseeing model development, and ensuring successful production implementation. The director also aligns AI initiatives with business goals and drives measurable outcomes.

2. What types of AI solutions are typically managed in this role?
Solutions may include predictive analytics, natural language processing, computer vision, and automation systems. These applications are often embedded into products or operational workflows. The focus is on delivering practical, business-driven AI solutions rather than purely experimental models.

3. How does this role collaborate with technical and business teams?
The director works closely with data scientists, engineers, product leaders, and business stakeholders. Collaboration ensures AI solutions are technically sound and aligned with real-world needs. The role acts as a bridge between strategy and execution.

4. What level of technical expertise is required for this role?
A strong understanding of machine learning, data engineering, and AI system architecture is essential. While not always hands-on, the ability to guide technical decisions and evaluate solutions is critical. Familiarity with cloud platforms and MLOps practices is often required.

5. How is success measured in this role?
Success is measured by the business impact of AI initiatives, such as revenue growth, cost savings, or operational efficiency. Model performance, adoption rates, and scalability are also key metrics. Delivering production-ready, reliable AI solutions is critical.