Roles & Responsibilities:
• Translate supply chain, manufacturing, quality, engineering, and finance requirements into reliable system workflows, data models, forms, approvals, exception logic, permissions, and operating procedures.
• Design and implement agentic and AI-enabled workflows that help track supplier commitments, purchase order status, material readiness, action items, nonconformances, expediting needs, open risks, and required follow-ups.
• Implement anomaly detection algorithms to identify gaps in quality processes and help prioritize system architecture improvements.
• Build practical automations using SQL, Python, APIs, low-code tools, Robotic Process Automation, webhooks, or workflow engines to reduce manual status chasing and improve execution visibility across internal teams and suppliers.
• Develop human-in-the-loop AI workflows that can summarize communications, extract commitments, propose next actions, draft follow-ups, flag missing data, and escalate exceptions throughout enterprise systems while preserving user accountability and review.
• Own day-to-day administration, configuration, and improvement of supply chain and manufacturing enterprise systems, including MES, purchasing/procurement systems, ERP/MRP modules, supplier portals, inventory/material systems, and related operational tools.
• Create integrations between enterprise systems and collaboration tools such as email, Slack/Teams, ticketing systems, document repositories, supplier portals, spreadsheets, and internal applications.
• Maintain master data and system hygiene for suppliers, parts, BOMs, routings, purchase orders, work orders, inspection status, ownership, lead times, milestones, and operational metadata.
• Support implementation and rollout of new tools or modules, including requirements gathering, vendor coordination, configuration, testing, migration, user acceptance testing, training, and post-launch support.
• Partner with supply chain and manufacturing teams to build workflows for PO release, supplier onboarding, supplier execution reviews, material readiness, receiving, inspection, nonconformance handling, change/containment impact analyses, and production handoffs.
• Create repeatable process documentation, system runbooks, automation specs, change logs, training materials, access-control guidance, and audit evidence that support regulated and government-facing operations.
• Monitor workflow performance and system adoption, proactively identifying bottlenecks, data-quality issues, broken integrations, and opportunities to simplify or automate operational work.
• Own practical data quality and exception-management routines so AI workflows act on trusted information, produce auditable outputs, and route edge cases to the right accountable owners.
• Incorporate and grow unit and integration testing for the enterprise software suite and internal tools developed as part of the role.
• Partner with database architects and system administrators to design and develop extract, transform, and load pipelines from various source systems into optimized formats for AI-enabled processing.