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Cognite is seeking a Tech Lead for its Supply Chain Center of Excellence to own the technical architecture of an integrated supply chain offering built on knowledge graphs, generative AI agents, and command-center UX. You will serve as the subject-matter expert across source-make-deliver processes, modeling customer supply chains and demonstrating how AI and UI tools transform integrated data graphs into deviation triage and resolution workflows.
You will be equally comfortable in C-level value conversations and technical deep-dives on data models and agent skills. The role goes beyond AI prompting—you will engineer domain expertise into testable, deterministic playbooks, treating CoE knowledge as a rigorous system with guardrails, ground-truth testing, and staged rollouts.
Key responsibilities include:
- Aligning the CoE on high-impact use cases (e.g., delayed inbound spare parts leading to maintenance delays and order risk) and deploying them as demos or customer solutions
- Leading customer modeling sessions to demonstrate how domain data models and complex hierarchies absorb requirements securely and at scale
- Guiding customers on adopting the graph/AI/UI stack, including integration patterns with Snowflake, Databricks, and ERPs
- Authoring AI skills with fixed parameters, guardrails, and testable anchors, keeping data models and agent logic aligned
- Serving as escalation point for complex graph queries and agent/UI design; owning testing and evaluation frameworks
- Supporting end-to-end architecture reviews and quantifying commercial impact for executive business cases
- Equipping partners with reusable demos and accelerators; maintaining clear terminology across models, docs, and AI logic
Required qualifications include deep knowledge of industrial supply chain planning/execution and ISA-95/88 and SCOR frameworks; 5–7 years in industrial supply chain roles and 5–7 years in pre-sales, solution architecture, or delivery for enterprise software; experience designing industrial information/knowledge-graph data models; hands-on proficiency in Python and frontend technologies (TypeScript/React) with strong engineering discipline; a systemic AI/testing mindset with rigorous multi-stage evaluation and root-cause debugging; excellent client-facing skills; and familiarity with modern data platforms and agentic AI/LLM workflow design.
