Industrial AI Solution Engineer

Core Responsibilities

Partner with Account Executives to prioritize strategic opportunities and act as the technical lead for complex engagements. Key responsibilities include:

• Client Engagement & Fast AI Prototyping: Move clients from high-level strategy to live, functioning versions of Cognite’s solutions using Fast AI Prototyping via Cognite Atlas AI™ and Cognite Data Fusion®.
• Agentic Solution Development: Lead the design and implementation of first-of-their-kind industrial agents. Leverage the Atlas AI workbench to automate complex industrial workflows, ensuring solutions are technically feasible, scalable, and grounded in the contextualized data foundation of our Industrial Knowledge Graph.
• Technical Representation & Use Case Design: Lead use case workshops and briefings, translating functional and non-functional requirements into deliverable high-level use cases. Build executive confidence by delivering client-focused demos and reference architectures that prove the ROI of Industrial AI.
• Product Innovation & Field Leadership: Act as the critical bridge between the field and Cognite’s Product organization. Translate field friction and deployment learnings into actionable product requirements and scalable best practices that strengthen Cognite’s position as the leader in Industrial DataOps.

Key Impact Areas

• Industrial Architecture Expertise: Design scalable architectures that unify siloed IT/OT/ET data into a single source of truth using Cognite Data Fusion®.
• Agentic AI Proficiency: Demonstrated experience building with LLMs (Gemini, Claude, GPT-4) and a deep understanding of the Agentic AI landscape to create trusted, mission-critical industrial agents via Cognite Atlas AI™.
• Full-Stack Solution Engineering: Orchestrate and build end-to-end prototypes integrating GenAI components, CDF data models, and legacy customer systems using scalable software practices and open-source AI frameworks.
• Technical Evangelism & Strategic Influence: Distill complex technical AI solutions into compelling, value-driven narratives. Pivot seamlessly between deep architectural sessions with engineers and strategy briefings with C-level executives.

Required Qualifications

• 3+ years in forward-deployed engineering/pre-sales engineering roles, ideally in enterprise SaaS, cloud platforms, or industrial software companies.
• Strong engineering background, preferred fields include Computer Science, Mathematics, Software Engineering, Physics, and Machine Learning.
• A strong foundation in Python and a deep understanding of the GenAI landscape (embeddings, RAG, and prompt chaining).
• Excellent problem-solving, analytical, and communication skills.
• Ability and interest to travel up to 50% as needed.

Preferred Experience

• Education or experience in the industrial space (e.g., Petroleum, Chemical, Mechanical, or Control System Engineering).
• Previous customer-facing or sales experience.
• Experience working with messy real-world variables from industries like Energy, Oil and Gas, Chemicals, Life Sciences, and Discrete.
• Excited to bridge the gap between traditional heavy industry and the future of Autonomous Operations via Cognite Data Fusion® and Agentic AI.