AI Engineer

• Location 191 AMERICAN BLVD STE 300,WESTLAKE, OH, ,United States

Reports to:

Director of Data Enablement |

Location:

Westlake, OH | Hybrid

The Data & AI Solutions Engineer designs, builds, and supports advanced analytics and AI-enabled solutions that turn Palmer Holland's governed lakehouse data into measurable business value.

Reporting to the Director of Data Enablement, this role works at the intersection of data engineering, advanced analytics, applied AI, and business problem-solving. The role focuses on building practical, scalable solutions for high-value business needs such as strategic pricing, margin leakage analysis, supplier price-change workflows, order remark classification, touchless order enablement, and executive KPI modernization.

This role partners closely with IT, which owns Databricks as an enterprise technology platform, including infrastructure, integrations, security architecture, CI/CD frameworks, and environment provisioning. The Data & AI Solutions Engineer contributes to solution design, analytical modeling, AI workflow development, evaluation, monitoring, and production readiness in alignment with those standards.

• Advanced analytics and AI-enabled solution development within the governed lakehouse environment.
• Predictive, machine learning, and AI-assisted workflows that support business decision‑making.
• Reusable patterns for moving data and AI use cases from prototype to governed production rollout.
• Analytical models and feature engineering for priority use cases.
• AI evaluation, monitoring, confidence scoring, and human‑in‑the‑loop design.
• Documentation of solution logic, assumptions, testing methods, and business impact.
• Technical partnership with the Analytics Product Engineer to turn models and insights into usable analytics products.

This role works closely with IT and App Development but does not own Databricks infrastructure architecture, core‑system integrations, security architecture, identity/access management, enterprise CI/CD frameworks, environment provisioning, ERP/CRM systems of record, or source‑system data quality enforcement at the pipeline level.

• Design and build advanced analytics solutions that support high‑priority business problems.
• Develop analytical models for strategic pricing, margin leakage, price realization, customer behavior, supplier price changes, and other commercial and operational use cases.
• Build repeatable solution patterns that can be reused across domains rather than one‑off analytical work.
• Operational workflow automation: agentic and AI‑assisted solutions that reduce manual back‑office effort across order management, procurement, and logistics operations — including intelligent document processing, exception‑based triage, and touchless workflow enablement.
• Translate business needs into technical solution designs in partnership with the Director of Data Enablement, IT, and business stakeholders.

• Build and support predictive models and AI‑assisted workflows using governed data from the lakehouse.
• Develop feature engineering approaches for use cases such as pricing intelligence, churn/customer health, product or customer segmentation, and order automation.
• Create evaluation methods, golden datasets, test cases, and monitoring processes for AI‑enabled solutions.
• Design human‑in‑the‑loop processes where AI outputs require review, approval, or exception handling.
• Partner with IT on production deployment standards, logging, monitoring, operational readiness, token optimization, and cost control.

• Build solutions that use curated, trusted, and certified datasets to solve practical business problems.
• Contribute to silver‑layer modeling and transformation work in partnership with IT, where advanced analytics or AI solutions require conformed, business‑ready data structures not yet available in the governed layer.
• Support development of gold‑layer analytical outputs in partnership with the Director of Data Enablement and domain stakeholders.
• Contribute to semantic modeling and…