Supply Chain Tech - Center of Excellence

About This Role

This role involves leading the technical development of Cognite's Integrated Supply Chain offering, focusing on the knowledge graph, generative AI agents, and command-center user experience. The ideal candidate will be a subject-matter expert across the entire supply chain, capable of modeling customer supply chains and demonstrating how AI and UI tools can transform an integrated graph into a system for deviation triage and resolution. The position requires comfort in both C-level value discussions and technical sessions on data models or agent skills, with an emphasis on engineering domain expertise into testable and deterministic playbooks.

Responsibilities

• Align the Center of Excellence (CoE) on high-impact use cases and deploy them as demos or customer solutions
• Lead customer modeling sessions, demonstrating how domain data models and complex hierarchies securely absorb requirements at scale
• Guide customers on adopting the graph/AI/UI stack, including integration patterns and the importance of agents grounded in deterministic graph paths
• Translate domain expertise into structured AI skills with fixed parameters, guardrails, and testable anchors, ensuring alignment between data models and agent logic
• Serve as an escalation point for complex graph queries and agent/UI design; own testing and evaluation frameworks, rigorously classifying failures before modifying agent logic
• Support end-to-end architecture reviews and quantify commercial impact for executive business cases
• Equip partners with reusable demos and accelerators; maintain clear, consistent terminology across models, documentation, and AI logic

Requirements

• Deep knowledge of industrial supply chain planning/execution and its links to production, quality, and maintenance; fluency with ISA-95/88 and SCOR frameworks
• 3+ years in industrial supply chain (planning, logistics, inventory) and 5+ years in pre-sales, solution architecture, or delivery for enterprise software
• Experience designing industrial information/knowledge-graph data models (temporal relations, typed hierarchies) and integrating structured/unstructured enterprise data
• Hands-on proficiency in Python and frontend (TypeScript/React), with strong engineering discipline (ADRs, automated testing, CI/CD)
• Systemic AI/testing mindset: optimized tool routing, rigorous multi-stage evaluation, root-cause debugging, and graceful handling of edge cases
• Excellent client-facing skills, able to translate complex data/AI concepts for audiences from engineers to C-level executives
• Familiarity with modern data platforms (Snowflake, Databricks, Spark/SQL), source systems (ERP/MES/WMS/TMS), and agentic AI/LLM workflow design
• Prior experience in high-growth (startup/scale-up) environments
• Bachelor's degree or equivalent practical experience