Senior Principal Data, Analytics & AI Engineer

Quick Facts - Senior Principal, hands-on data/analytics/AI engineering role within a global supply chain and manufacturing context - Focus: near-real-time data modernization and agentic AI that powers multi-agent decision support Description Own the technical design and end-to-end delivery of agentic AI and data modernization solutions across global supply chain and MQ. Build multi-agent workflows that correlate supply chain and manufacturing signals from disconnected systems and provide actionable insight used by teams running production. Provide technical leadership, standards, and mentoring while ensuring agent evaluation, observability, and responsible AI guardrails. Responsibilities - Lead architecture for agentic AI and data modernization from problem framing through production support - Define reusable standards for cloud data modeling, pipeline design, agent orchestration, and evaluation - Mentor engineers; lead code and design reviews - Partner with business and IT stakeholders to shape roadmaps and delivery sequence; manage build/buy and vendor/partner delivery - Develop deep knowledge of supply chain data domains and analytics (e.g., material master, BOM/recipe, procurement, inventory movements, production orders/batch execution, planning/scheduling, logistics, quality/deviations) - Translate ERP semantics into trusted data models across SAP and SHARP - Correlate ERP, planning, MES, historian, and quality data across systems and time to answer questions no single system can - Design, build, and deploy AI agents and multi-agent workflows for automation of analysis and decision support (prompt engineering, tool/function calling, orchestration, RAG) - Define agent performance measurement (tests, evaluation criteria, accuracy/hallucination monitoring, feedback loops, observability, guardrails) - Implement and deploy machine learning/predictive models into production with performance, scalability, and interpretability - Build scalable data pipelines (modern ETL/ELT) for advanced analytics and agentic AI - Lead data modernization to migrate/reshape legacy supply chain assets to modern lakehouse/cloud architectures - Monitor and troubleshoot data quality and agent behavior; ensure integrity and reliability - Maintain documentation for data architecture, flows, agent designs, prompts, model choices, and deployments to support maintainability and GxP/CSV - Ensure compliance with data privacy, security, and responsible AI requirements Benefits - Comprehensive benefits package including 401(k), pension, vacation, medical/dental/vision/prescription coverage, flexible benefits, life insurance, time-off/leave benefits, and well-being benefits - Eligibility to participate in a company-sponsored 401(k) and potential company bonus (depending on performance) formatted_html_description: Quick Facts

Quick Facts

• Senior Principal, hands-on data/analytics/AI engineering role within a global supply chain and manufacturing context
• Focus: near-real-time data modernization and agentic AI that powers multi-agent decision support

Description

Own the technical design and end-to-end delivery of agentic AI and data modernization solutions across global supply chain and MQ. Build multi-agent workflows that correlate supply chain and manufacturing signals from disconnected systems and provide actionable insight used by teams running production. Provide technical leadership, standards, and mentoring while ensuring agent evaluation, observability, and responsible AI guardrails.

Responsibilities

• Lead architecture for agentic AI and data modernization from problem framing through production support
• Define reusable standards for cloud data modeling, pipeline design, agent orchestration, and evaluation
• Mentor engineers; lead code and design reviews
• Partner with business and IT stakeholders to shape roadmaps and delivery sequence; manage build/buy and vendor/partner delivery
• Develop deep knowledge of supply chain data domains and analytics (material master, BOM/recipe, procurement, inventory movements, production orders/batch execution, planning/scheduling, logistics, quality/deviations)
• Translate ERP semantics into trusted data models across SAP and SHARP
• Correlate ERP, planning, MES, historian, and quality data across systems and time to answer business questions no single system can
• Design, build, and deploy AI agents and multi-agent workflows (prompt engineering, tool/function calling, orchestration, RAG over technical documents and operational data)
• Define agent performance measurement and improvement (test scenarios, evaluation criteria, accuracy and hallucination monitoring, feedback loops, observability, guardrails)
• Implement and deploy machine learning/predictive models into production with performance, scalability, and interpretability
• Build scalable data pipelines using modern ETL/ELT to support advanced analytics and agentic AI
• Modernize legacy supply chain reporting/data assets and migrate to lakehouse and cloud architectures
• Monitor and troubleshoot data quality and agent behavior to ensure data integrity and reliability
• Maintain documentation for data architecture, flows, agent designs, prompts, model choices, and deployments to support maintainability and GxP/CSV
• Ensure compliance with data privacy, security, and responsible AI requirements

Benefits

• Comprehensive benefits including 401(k), pension, vacation, medical/dental/vision/prescription coverage, flexible benefits, life insurance, time-off/leave benefits, and well-being benefits
• Potential eligibility for a company bonus (depending on company and individual performance)