Director - Applied AI Engineering - Erlanger, KY

Director - Applied AI Engineering - Erlanger, KY
This is an exempt level position
Position Summary:
ADM Global Technology is accelerating ADM’s transformation through AI-powered solutions that create measurable business value. Applied AI Engineering is at the center of this mission — building the intelligent products and capabilities that help ADM operate smarter, faster, and more effectively across its global business.
We are seeking a “Director – Applied AI Engineering” to lead the team responsible for building AI solutions that directly address business needs across ADM. This leader will own the end-to-end delivery of AI products and capabilities — from discovery and scoping through production — and will build and scale a high-performing team of Applied AI Engineers. The Director will serve as the primary bridge between business partners and AI execution, ensuring that use cases are well-defined, solutions are delivered with rigor, and outcomes are measurable. Expertise in building and shipping AI solutions is the core requirement; familiarity with AI platforms, cloud infrastructure, and architecture is a plus that will strengthen the team’s delivery capability.

Key Responsibilities:

• Lead the Applied AI Engineering team in designing, building, and delivering AI-powered solutions that directly address business priorities across ADM’s global operations.
• Own the AI solution delivery lifecycle — from use case identification and scoping through rapid prototyping, MVP development, and production-grade deployment — ensuring consistent quality, speed, and business alignment.
• Partner with business leaders, product owners, and cross-functional stakeholders to build a prioritized pipeline of high-value AI use cases, maintaining clear alignment between engineering delivery and business outcomes.
• Build and develop a team of Applied AI Engineers; attract top talent, set clear expectations, provide ongoing coaching and performance feedback, and create a culture of technical excellence and continuous learning.
• Own the budget and headcount plan for the Applied AI Engineering function — including annual planning, vendor contracts, tooling investments, and ongoing resource allocation to ensure the team is appropriately staffed and equipped to deliver.
• Define and own a 1–3 year capability and technology roadmap for Applied AI Engineering — articulating where the function is headed, what capabilities need to be built or acquired, and how the team’s investment connects to ADM’s broader digital and business strategy.
• Manage strategic vendor and partner relationships (e.g., Microsoft/Azure, OpenAI, and third-party AI solution providers), including performance management, contract oversight, and identification of partnership opportunities that accelerate the team’s delivery.
• Collaborate with the Advanced Analytics and Data Engineering teams to ensure the data foundations required for AI solutions are in place and well-structured.
• Work in close partnership with AI Platform Engineers and AI Architects to ensure that solutions built by the Applied AI team are deployed on durable, scalable, and secure foundations.
• Define and uphold engineering standards for the Applied AI team, including code quality, model evaluation rigor, documentation practices, and responsible AI principles.
• Serve as a senior technical voice and thought leader on applied AI within the Digital & Innovation organization, advising on the appropriateness of AI approaches for given business problems and championing pragmatic, high-impact execution.
• Communicate progress, milestones, risks, and outcomes to executive and senior leadership stakeholders; translate technical work into business language clearly and confidently.
• Stay at the forefront of advancements in Generative AI, machine learning, and AI tooling — continuously identifying opportunities to improve team capabilities and solution quality.
• Champion responsible AI practices, ensuring that all solutions reflect ADM’s values and comply with relevant AI governance, data privacy, and regulatory requirements.

Standard Job Requirements:

• Applied AI Leadership: Demonstrated track record leading teams that build and deliver AI-powered products and solutions in production. Comfort operating at the intersection of business strategy and technical execution.
• Generative AI & ML Expertise: Deep hands-on understanding of Generative AI techniques (Prompt Engineering, RAG, fine-tuning, agentic frameworks) and classical machine learning approaches. Ability to guide teams in selecting the right methods for the right problems. Familiarity with commercial and open-source models and frameworks (e.g., Claude, Open AI, Google Vertex, AWS Bedrock, Azure foundry, LangChain, LlamaIndex, HuggingFace).
• Solution Delivery Discipline: Proven ability to drive structured AI solution delivery — from ambiguous business problems through working production systems — with a strong focus on measurable business value.
• People & Team Development: Experience building, growing, and leading high-performing engineering teams. Strong coaching instincts and the ability to attract and retain exceptional AI engineering talent.
• Business Partnership: Ability to engage credibly and effectively with senior business stakeholders — shaping use cases, setting expectations, presenting options, and communicating outcomes with clarity and influence.
• Platform & Architecture Awareness: Working knowledge of cloud environments (preferably Azure), AI/ML platforms, and deployment concepts is advantageous. Not required to be the deepest technical expert in infrastructure, but must be conversant enough to partner effectively with AI Platform Engineers and AI Architects.
• Responsible AI & Governance: Understanding of responsible AI principles, data privacy considerations, and the governance frameworks relevant to enterprise AI deployment.

Education, Experience & Soft Skills:

• Bachelor’s degree (Master’s preferred) in Computer Science, Data Science, Engineering, or a related field.
• Minimum 12 years of experience in IT including minimum 7+ years of experiance with AI, machine learning, deep learning, with at least 5+ years in a leadership or management role overseeing AI engineering teams or delivery functions.
• Experience leading teams that ship AI-powered products or capabilities to internal or external users, with demonstrated business impact.
• Strong executive presence; skilled at navigating organizational complexity and influencing decisions across business and technology stakeholders.
• Excellent communication skills, both written and verbal; able to represent the team’s work credibly at all levels of the organization.
• Strategic thinker with the ability to balance short-term delivery pressure with longer-term capability building.
• Proven ability to lead through ambiguity, set direction under uncertainty, and drive teams to high-quality outcomes in a dynamic environment.
• Industry knowledge within agriculture, commodities, supply chain, or manufacturing is a plus but not required.