Director of Applied AI

We’re looking for a Director of Applied A I who can find practical ways to use AI in our businesses. This is a hands‑on role for someone who is comfortable getting close to the business operation, asking good questions, writing code, building solutions, and implementing those solutions to help our teams to do better work, more efficiently.

The ideal candidate has built and shipped working AI or machine learning systems, knows how to measure whether they are useful in a business context, and can manage an iterative process of launching and optimizing the systems. The right person can sit with a long‑time expert in specialized industrial businesses, understand the work being done, and design a clear, efficient plan to implement AI in a meaningful way.

• Find practical places where AI or machine learning can make work better, faster, safer, or easier.
• Spend time with field and plant experts to understand how the work is done.
• Turn rough ideas and operational problems into clear requirements, automation prototypes, and implementation plans.
• Work with operations, technology, and leadership teams to choose the right problems and move useful work forward.
• Manage the technical product from first build through release for use in the business.
• Work with business leaders to decide how each system will be measured before and after it goes live.
• Build for reliability, security, maintainability, and day‑to‑day use.
• Keep up with new AI tools and release, continuously iterating and updating as appropriate.

Required Education, Experience, and

Qualifications:

• Successful launch of at one AI or machine learning system into existing business operations in the last 12 months.
• Experience building tools, workflows, automation, or data products used by non‑technical teams.
• Comfort working with senior leaders, technical teams, and people who have deep hands‑on knowledge of the work.
• Ability to explain, in plain language, how previous solutions and tools worked, what changed after launch, what broke, and what should be done differently next time.
• Can think across software, data, workflow, people, and operating constraints.
• Has worked directly with business or operations teams to define requirements.
• Can name an AI or machine learning release from the last month and explain what they did with it or how they evaluated it.
• Experience in industrial, field, logistics, manufacturing, energy, construction, or another operations‑heavy environment.

Application Requirement
:

Please include a one‑page report describing one AI or machine learning system that you made a significant contribution to that was put into production, how you knew it worked, what broke or changed after release, and what you learned that will be applied in your next build.