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Cognite is an industrial AI and data platform company focused on digital transformation and operational improvements across demanding industrial environments. The Context Services team converts unstructured industrial data into structured, actionable intelligence for thousands of users.
You will serve as Principal Engineer and own the technical architecture for Context Services, setting system-level direction that bridges AI Engineers and the central Platform Engineering team. This is the senior-most technical voice in the group, responsible for architecture decisions that other engineers build against.
Key responsibilities include:
- Define end-to-end system architecture for Context Services; design low-latency APIs and services supporting thousands of concurrent users with sub-second response times
- Partner with product, architecture, and engineering leadership to translate complex industrial data problems into scalable, sequenced technical strategy
- Architect frameworks for model serving, vector databases, and agentic workflows, including reliable state management, prompt tracking, and orchestration-layer design
- Serve as primary technical liaison with the central Platform team, defining how Context Services leverages and extends core infrastructure
- Set engineering standards and review practices; mentor Senior and mid-level engineers; unblock the hardest cross-cutting technical problems
- Drive technical innovation through research, prototyping, and open-source contributions
You are a seasoned builder who designs fault-tolerant, scalable architectures from scratch and pushes the team toward production-grade best practices. You balance technical rigor with business reality, anticipate system bottlenecks, make hard architectural trade-offs, and translate business goals into executable technical strategy. You take ownership of large, ambiguous projects from conception through deployment and mentor engineers along the way.
Required: Bachelor's or Master's degree in Computer Science, Data Science, or related field (PhD often preferred); 10+ years of industry experience in machine learning and software development; strong programming skills in Python, C++, or Java with deep proficiency building high-concurrency, asynchronous applications.
