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.
We´re looking for a Senior AI native designer for our Cognite Oslo team that will improve, invent, prototype, and scale next-generation product experiences for Cognite Data Fusion (CDF), within the Knowledge Graph area.
As a Senior Product Designer, you will shape how industrial data is modeled, stored, governed and made actionable through AI-empowered workflows. You’ll move from insight → concept → working experience with speed and clarity, partnering closely with product, engineering, strategy, and customers to design intelligent systems that sit at the core of CDF.
You are hands-on, systems-oriented, and fluent in AI. You understand how agents, tools, and data pipelines work together. You design trustworthy, human-in-the-loop experiences that operate reliably under real-world constraints and deliver measurable business impact.
Product Design Excellence
- Design AI-empowered industrial experiences that span data storage, modelling and data governance of industrial data.
- Prototype with real data and real models by testing on real world industrial use cases with your users and product counterparts; validate flows under realistic latency, streaming, reliability, and cost constraints.
- Design for probabilistic systems operating on imperfect data: handle schema ambiguity, partial ingestion failures, conflicting signals, and uncertainty.
- Define patterns for human-in-the-loop supervision across data mapping, anomaly detection, enrichment, and agent-driven automation.
- Express ideas at multiple fidelities: from system diagrams and agent/tool contracts to interactive prototypes, micro-workflows, and production-ready UI.
- Partner with product strategists and business designers to evaluate desirability, feasibility, and viability; shape experience KPIs tied to adoption, data quality, reliability, and operational efficiency.
- Tell compelling stories through narratives, visuals, and prototypes that make complex data systems understandable and shippable.
- Lead design sessions and facilitate cross-functional workshops to align around architecture, workflows, and long-term product vision.
Design Execution & Ownership
- Own outcomes end-to-end from discovery through shipped experience, including research plans, flows, information architecture, interaction patterns, and system-level design decisions.
- Operationalize AI in the UX: define agent and tool contracts, escalation paths, monitoring hooks, logging requirements, and feedback loops to continuously improve system quality and cost efficiency.
- Collaborate tightly with engineering to scope increments, de-risk technically complex integrations early, and land high-craft solutions within platform constraints.
- Establish scalable design patterns for data-heavy workflows and evolve the design system thoughtfully as new integration use cases emerge.
- Drive clarity in ambiguous, cross-functional environments and make well-reasoned design decisions that balance user value, reliability, performance, and cost.
- Continuously validate solutions through user research, usability testing, and experiment design; make evidence-based tradeoffs across usability, automation, and operational risk.
Contribute to best practices for AI-native product design and help shape how Data Integrations evolve over time.
- 5+ years of product design experience, with demonstrated ownership of complex, data-heavy or AI-powered systems.
- Strong understanding of AI-native workflows, including prompt design, tool/agent orchestration, RAG patterns, and model/runtime constraints such as latency and token/cost budgets.
- Experience designing products that operate on structured and unstructured data, including ingestion, transformation, schema mapping, or data pipeline workflows.
- Hands-on prototyping experience using real data sources, APIs, SDKs, lightweight code, or no/low-code tools to validate feasibility and user experience.
- Demonstrated ability to design for probabilistic and imperfect systems, including error states, uncertainty handling, trust patterns, and human-in-the-loop supervision.
- Strong user research skills: ability to plan and run studies, synthesize qualitative and quantitative insights, and translate findings into actionable product direction.
- Excellent communication, facilitation, and stakeholder management skills; able to collaborate effectively with engineering-heavy teams and present complex ideas clearly to executives and customers.
- Proven ability to work in ambiguous, fast-paced environments with a bias for action and structured decision-making.
- A portfolio showcasing end-to-end ownership, systems thinking, and thoughtful design of complex workflows.
- 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 Required
- 5+ years of product design experience, including ownership of complex, data-heavy or AI-powered systems.
- Strong understanding of AI-native workflows, including prompt design, tool and agent orchestration, RAG patterns, latency constraints, and token or cost budgets.
- Experience designing products using structured and unstructured data, including ingestion, transformation, schema mapping, or data pipeline workflows.
- Hands-on prototyping experience with real data sources, APIs, SDKs, lightweight code, or no-code/low-code tools.
- Experience designing for probabilistic and imperfect systems, including error states, uncertainty handling, trust patterns, and human-in-the-loop supervision.
- Strong user research skills, including planning and running studies, synthesizing qualitative and quantitative insights, and translating findings into product direction.
- Excellent communication, facilitation, and stakeholder management skills, including collaboration with engineering-heavy teams and presentations to executives and customers.
- Ability to work in ambiguous, fast-paced environments with a bias for action and structured decision-making.
- Portfolio demonstrating end-to-end ownership, systems thinking, and thoughtful design of complex workflows.
Cognite Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Cognite and has not been reviewed or approved by Cognite.
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Affordable Benefits — Healthcare premiums for employees and dependents are often fully covered, reducing out‑of‑pocket costs. Feedback suggests this makes the total rewards feel competitive in key markets.
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Parental & Family Support — Paid parental leave for primary and secondary caregivers is described as generous. This signals a family‑friendly approach that many consider a standout perk.
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Leave & Time Off Breadth — Unlimited PTO with a company‑wide year‑end shutdown offers ample time away from work. Flexible time‑off options are consistently highlighted across U.S. roles.
Cognite Insights
What We Do
Cognite is an AI company that delivers industrial software to improve the production efficiency of Energy, Process Manufacturing, and other industrial companies. We deliver an Industrial DataOps platform that liberates siloed data and empowers our customers to solve some of their most complex business problems with AI-powered solutions. The typical solutions we enable drive innovative new ways to approach Data Exploration, Digital Operator Rounds, Production Optimization, Turnaround Planning, and Root Cause Analysis. We do this by automating and scaling industrial data contextualization of various sources (such as time series, engineering diagrams, equipment logs, maintenance records, 3D facility models, images, large point clouds, and more). We use AI and other tools to find and map the meaningful relationships between the data across these various sources. In addition, we provide intuitive tools that enable efficient use of analytics and automated workflows, as well as prebuilt AI capabilities and a low-code industrial agent builder, Cognite Atlas AI, that enables AI to carry out more complex operations with greater accuracy.
Why Work With Us
Employees at Cognite are pushing the envelope with the latest cloud technology, scaling industrial applications across hundreds of assets, revolutionizing industrial data models, and working with robotics. Cogniters are fast, creative, and resilient. We keep the energy high and fun, learning from our mistakes and celebrating our victories together.
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