AI Solution Engineer

About Cognite & ATLAS AI

Cognite is a global industrial AI software-as-a-service (SaaS) company supporting the full-scale digital transformation of heavy-asset industries around the world. Our core product, Cognite Data Fusion (CDF), is a leading industrial DataOps platform. Building on CDF, ATLAS AI is our innovative offering designed to deliver bold, customer-centric innovation powered by artificial intelligence.

The Role

As an

AI Solutions Engineer , you will bridge the gap between industrial challenges and AI capabilities. You will lead the rapid prototyping of GenAI-powered solutions, design user-facing interfaces, and orchestrate intelligent agent workflows in real customer contexts. You’ll work closely with customer teams, internal stakeholders, and product / engineering to craft lighthouse solutions that demonstrate what’s possible with ATLAS AI.

This role requires hands-on technical depth, creativity in solution design, and the ability to operate fluidly across domains, tools, and stakeholders.

Responsibilities

End-to-End Prototyping

Build cross-stack prototypes using ATLAS AI, CDF, and open-source AI frameworks to solve real customer challenges.

Agent Workflow Design

Design and implement multi-agent workflows that combine LLMs, tool use, and reasoning over industrial data.

Customer-Facing Execution

Collaborate directly with technical teams at customer sites to refine use cases and integrate solutions in real environments.

Interactive UI Development

Build lightweight but powerful UIs that showcase value to executives and operators alike.

System Integration

Orchestrate integration between GenAI components, CDF data models, and existing customer systems using scalable software practices.

Evangelism & Enablement

Translate technical solutions into compelling narratives that inspire stakeholders across both internal and external audiences.

What We’re Looking For

Must-Have Skills

5+ years of experience in software engineering, AI solution architecture, or similar roles.

Proven hands-on experience with GenAI systems (LLMs, embeddings, prompt chaining, etc.).

Experience building LLM-driven or agent-based applications (e.g., LangChain).

Solid full-stack development skills, including :

Frontend : React (or similar frameworks) for building interactive UIs.

Backend : Python (or similar) for data orchestration and API integration.

Ability to work across the stack and own the delivery of functional, user-facing solutions.

Strong communication and storytelling skills for both technical and executive audiences.

Proven ability to write clean, maintainable, and scalable code, following engineering best practices for testing, version control, and review.

A maker mindset

with bias toward rapid iteration, showing rather than telling, and learning by doing.

Bonus Skills

UI / UX sensibilities for building demo interfaces and apps quickly.

Understanding of industrial data types (e.g., time series, industrial knowledge graphs).

Experience with Cognite Data Fusion.

Familiarity with vector databases and RAG pipelines.

Cloud-native development experience (AWS, Azure, etc.).

Exposure to industrial use cases or previous work in industrial analytics or engineering domains.