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
- 3+ 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.