AI Solution Engineer
4 days ago
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.
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