Director, Data & AI

Brilliant®; Cleveland (OH); On-site; USD 170,000 - 210,000; Full time

Job summary

Brilliant is seeking a Director of Data & AI to build and lead our data intelligence and artificial intelligence capability across supply chain and logistics. This is a hands-on leadership role translating operating challenges—inventory optimization, demand forecasting, warehouse throughput—into a modern data and AI roadmap and leading a team to deliver it.

You will own strategy, architecture, governance, and vendor relationships, partnering with IT leadership, business units, and our SAP

Qualifications

• 8+ years in data, analytics, or AI leadership roles, including 3+ years managing teams.
• Direct experience in supply chain, logistics, or manufacturing with demand planning and inventory operations.
• Proven expertise in data governance and data engineering across data platforms and ETL/ELT.
• Knowledge of AI architecture, multi‑agent systems, and responsible AI practices.

Responsibilities

• Set data & AI strategy and multi‑year roadmaps aligned to supply chain priorities.
• Build enterprise data foundation: architecture, pipelines, governance, security.
• Lead ML/AI delivery including model deployment and monitoring for core use cases.
• Architect for cloud and edge environments across distributed sites.
• Establish governance frameworks and promote ethical, compliant AI practices.
• Hire, mentor, and grow a high‑performing data/AI team.
• Partner with business units to drive adoption and calculate business value.
• Manage vendor relationships and build build/buy strategies.
• Present strategy and impact to senior leadership.

Skills

Data leadership

Strategy & governance

Team leadership

Communication

Cloud architecture

ML/AI delivery

Stakeholder mgmt

Education

Bachelor's degree in CS/DS/Engineering

Tools

SAP S/4HANA

AWS/Azure/GCP

Job description

Director of Data & AI to build and lead our data intelligence and artificial intelligence capability. This is a hands‑on leadership role for someone who can translate supply chain and logistics operating challenges — inventory optimization, demand forecasting, warehouse throughput, supplier risk, pricing — into a modern data and AI roadmap, and who can lead a team to deliver it.

You will own the strategy, architecture, and governance for data and AI across the organization, working closely with the VP of IT, business unit leaders, and our SAP S/4HANA Public Cloud program to ensure data and AI investments are built on a clean, governed foundation and deliver measurable business value.

What You'll Do

• Set the data & AI strategy. Define and lead a multi-year roadmap for data intelligence, machine learning, and AI/agentic AI capabilities aligned to supply chain, warehouse, and manufacturing priorities.
• Build the data foundation. Own enterprise data architecture, data engineering pipelines, and data governance standards (data quality, lineage, master data, security, and compliance) across SAP S/4HANA and adjacent systems.
• Lead AI and machine learning delivery. Direct the design, development, and deployment of ML models, predictive analytics, and agentic AI solutions for use cases such as demand planning, inventory optimization, logistics/warehouse operations, and supplier/customer intelligence.
• Architect for scale. Define the technical architecture spanning cloud and edge computing environments, ensuring solutions are secure, scalable, and cost‑effective across distributed manufacturing and distribution sites.
• Establish governance and trust. Stand up data governance and AI governance frameworks — policies, standards, and review processes that ensure data integrity, model performance, ethical AI use, and regulatory compliance.
• Lead and grow the team. Hire, mentor, and manage a team of data engineers, data scientists, and ML/AI practitioners; foster a culture of technical excellence and business partnership.
• Partner across the business. Work directly with supply chain, operations, finance, and plant leadership to identify high‑value use cases, build business cases, and drive adoption of data and AI solutions.
• Manage vendors and platforms. Evaluate and manage relationships with cloud, AI/ML, and analytics platform vendors; make build‑vs‑buy recommendations.
• Communicate to executives. Present strategy, progress, and business impact to senior leadership and the President in clear, non‑technical terms; build organizational buy‑in for data‑driven decision‑making.

What You Bring

Required:

• 8+ years of progressive experience in data, analytics, or AI leadership roles, including 3+ years managing teams
• Direct experience in the supply chain, logistics, or manufacturing industry, with a strong understanding of demand planning, inventory, warehouse, and distribution operations
• Proven expertise in data intelligence, machine learning, and data science — from problem framing through model deployment and monitoring
• Strong background in data governance (data quality, master data management, metadata, lineage, privacy/compliance) and data engineering (pipelines, data platforms, ETL/ELT, data warehousing/lakehouse architectures)
• Working knowledge of AI and agentic AI architecture — designing multi‑agent or autonomous AI systems, prompt/orchestration frameworks, and responsible AI practices
• Experience architecting solutions across cloud platforms (AWS, Azure, or GCP) and edge computing environments for distributed operations
• Excellent communication skills — able to translate technical concepts into business language for executives and operational leaders
• Demonstrated team leadership — hiring, developing, and managing high‑performing technical teams
• Bachelor’s degree in computer science, Data Science, Engineering, or related field (Master's preferred)

Preferred:

• Experience with SAP S/4HANA data models and integration, or other major ERP platforms
• Familiarity with modern AI/ML tooling (e.g., LLM platforms, vector databases, MLOps tooling, orchestration frameworks)
• Experience operating in a multi‑site manufacturing or distribution environment
• Track record of building a data/AI function from an early stage

What Success Looks Like in Year One

• A documented data & AI strategy and roadmap approved by IT and business leadership
• Foundational data governance standards and a data quality baseline established across priority domains
• At least one production AI/ML use case delivering measurable business value (e.g., inventory reduction, forecast accuracy improvement, operational efficiency gain)
• A capable, right‑sized team in place with clear roles and growth paths
• Strong, trusted working relationships with supply chain, operations, and finance leadership