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AI Engineer

Palmer Holland
Westlake, UAE
Full Time
Senior
Hybrid
4 weeks ago
PythonSQLDatabricksMachine LearningGenerative AIData Engineering
Free

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Brief Description

  • AI Engineer
  • Reports to: Director of Data Enablement | Location: Westlake, OH | Hybrid
  • Role Summary: 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.

What This Role Owns

  • 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.

Key Responsibilities

  • 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.
  • 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.

Priority Use Case Support

  • Strategic pricing and margin leakage: models and workflows that surface margin risk, price realization gaps, and pricing decision opportunities.
  • Fully loaded profitability analysis: scalable frameworks that trace sales through supply chain history to surface true pocket profitability.
  • FPL / supplier price change analysis: tools that compare supplier cost changes, identify material exceptions, and support pricing review workflows.
  • Order remark classification and touchless order enablement: AI assisted classification of order notes, remarks, and exception patterns to support Esker automation progress.
  • Executive KPI and certified dashboard modernization: analytical models and governed datasets that support trusted executive reporting.

Governance, Testing, and Production Readiness

  • Ensure AI and advanced analytics solutions are traceable, explainable, testable, and aligned with Palmer Holland governance standards.
  • Document model inputs, assumptions, limitations, evaluation methods, taxonomy, and business rules.
  • Partner with IT on release management, access controls, monitoring, and production deployment requirements.
  • Support responsible AI practices, including appropriate use of sensitive data, confidence thresholds, fallback logic, and auditability.

Required Qualifications

  • 5+ years of experience in data engineering, analytics engineering, applied AI, machine learning, data science, or advanced analytics solution delivery.
  • Strong SQL and Python skills.
  • Experience building analytical models or data products using enterprise data platforms.
  • Practical experience with AI, ML, or GenAI enabled applications, such as classification, prediction, recommendation, retrieval, evaluation, or workflow automation.
  • Experience with modern lakehouse or cloud data platforms such as Databricks (preferred), Snowflake, Azure, AWS, or similar environments.
  • Ability to translate ambiguous business problems into scalable analytical or AI enabled solutions.
  • Strong documentation habits and ability to explain technical concepts to business stakeholders.

Preferred Qualifications

  • Certification in or experience with Databricks, Delta Lake, Unity Catalog, MLflow, vector search, model serving, or similar technologies.
  • Experience with LLMOps, MLOps, AI evaluation frameworks, model monitoring, prompt/version control, or human in the loop workflows.
  • Experience in B2B distribution, specialty chemicals, ingredients, manufacturing, or regulated business environments.
  • Experience supporting pricing, order to cash, customer analytics, sales enablement, supply chain, or finance use cases.
  • Familiarity with data governance, semantic layers, certified datasets, and role based access controls.

Working Style

  • Practical builder who values business outcomes over technical novelty.
  • Comfortable working in shared ownership environments where IT, Data Enablement, and business teams each own part of the outcome.
  • Strong partner to IT, with respect for platform stability, security, deployment discipline, and change control.
  • Curious, analytical, and willing to challenge assumptions.
  • Able to move quickly without creating unnecessary risk.
  • Clear communicator who can explain what an AI or analytics solution does, how it was tested, and where human judgment is still required.

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