Supply Chain Tech Lead - Center of Excellence

Cognite is hiring a Supply Chain Tech Lead - Center of Excellence. Level rates it ; you can apply on Cognite.

Level's read on this job

Level rates this role Works on AI ●●●○: the daily work is on AI products, without building the model.
Tools and skills the posting cites include Databricks and AI agents.
Level classifies it as a lead role.
Level lists 53 other open roles at Cognite.

AI in this role

databricks

ai-agents

What Cognite is: Relentless to achieve

Cognite operates at the forefront of industrial digitalization, building AI, and data solutions that solve the world’s hardest, highest-impact problems. With unmatched industrial heritage and a comprehensive suite of AI capabilities, including low-code AI agents, Cognite accelerates the digital transformation to drive operational improvements.

We thrive in challenges. We challenge assumptions. We execute with speed and ownership. If you view obstacles as signals to step forward - not backwards - you’ll feel right at home here.

Our Moonshot is bold: Unlock $100B in customer value by 2035, and redefine how global industry works. Join us in this venture where AI and data meet ingenuity, and together, we will forge the path to a smarter, more connected industrial future.

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.

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.

Required Qualifications

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.

Learn more about us

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.

Equal Opportunity Cognite is committed to creating a diverse and inclusive environment at work and is proud to be an equal opportunity employer. All qualified applicants will receive the same level of consideration for employment.

How we rate this

Supply Chain Tech Lead - Center of Excellence at Cognite rates 69 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Supply Chain Tech Lead - Center of Excellence is an open job at Cognite.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in England, United Kingdom; Europe; France; Germany; Norway (Oslo).
The job was posted on September 3, 2026.
Seniority: lead.
Applications are handled by Cognite. Apply on Cognite

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agentsDatabricks

Questions you could be asked

How do you decide when an AI agent can act on its own versus asking for approval first?
Walk me through how you've used Databricks in your day-to-day work.
Describe a typical day in a role like this one: which parts run through AI directly?
If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

List these exact terms on your resume: AI agents and Databricks. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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