Cognite · Climate and energy
Supply Chain Tech Lead - Center of Excellence
- United Kingdom (Remote), +5 more: Europe, France, Germany, Norway, Oslo
AI roleAI EngineerBuilds with LLMs
Still open on Cognite's site · checked 4 hours ago
- Level
- Lead or manager
- Education
- Bachelor's degreeor equivalent experience
- Posted
What you'll do
As written by Cognite · Read the original
How you’ll demonstrate Ownership
As Tech Lead for the Supply Chain CoE, you own the technical spine of Cognite's Integrated Supply Chain offering — knowledge graph, generative AI agents, and command-center UX. You'll act as the subject-matter expert across source-make-deliver, modeling customers' supply chains and showing how AI/UI tools turn an integrated graph into deviation triage and resolution. You're equally comfortable in a C-level value conversation and a technical session on data models or agent skills. The bar goes beyond prompting AI: you'll engineer domain expertise into testable, deterministic playbooks — treating CoE knowledge as a rigorous system with guardrails, ground-truth testing, and staged rollouts.
Requirements
The Impact you bring to Cognite
- Solution & CoE Strategy: Align the CoE on high-impact use cases (e.g., delayed inbound spare → maintenance delay → order risk) and deploy them as demos or customer solutions.
- Knowledge-Graph Data Modeling: Lead customer modeling sessions; show how domain data models and complex hierarchies absorb requirements securely and at scale.
- Data & AI Architecture: Guide customers on adopting our graph/AI/UI stack, including integration patterns (Snowflake, Databricks, ERPs) and why agents must be grounded in deterministic graph paths.
- AI Skill-System Authorship: Turn domain expertise into structured AI skills with fixed parameters, guardrails, and testable anchors, keeping data models and agent logic aligned.
- Agentic Tooling & QA: Serve as escalation point for complex graph queries and agent/UI design; own testing and evaluation frameworks, classifying failures rigorously before changing agent logic.
- Enterprise Architecture & Value Selling: Support end-to-end architecture reviews and quantify commercial impact (orders at risk, delay penalties, landed costs) for executive business cases.
- Partner Enablement & Documentation: Equip partners with reusable demos and accelerators; maintain clear, consistent terminology across models, docs, and AI logic.
- 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 — not just prompting.
- 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.
- Impact 2025
- Cognite's Industrial AI: Moonshot
- We’re globally recognized domain experts with an international presence that spans Phoenix, Houston, Oslo Tokyo, Bengaluru, and Abu Dhabi.
Skills
Stack
- Python
- TypeScript
- React
- SQL
- Spark
Working languages
English
Company
Last checked . The details above were extracted automatically; the employer's original posting is the authority.
