About the Opportunity

The Impact you bring to Cognite

Key Responsibilities:

• Architecture & Scale: Define the system architecture for Context Services end-to-end; design low-latency APIs/services supporting thousands of concurrent users with sub-second response times.
• Cross-Functional Leadership: Partner with product, architecture, and engineering leadership to translate ambiguous industrial data problems into scalable, sequenced technical strategy.
• AI & LLM Orchestration: Architect the frameworks for model serving, vector databases, and agentic workflows, including reliable state management, prompt tracking, and orchestration-layer design.
• Platform Integration: Serve as the primary technical liaison with the central Platform team, defining how Context Services leverages and extends core infrastructure.
• Technical Standards & Mentorship: Set engineering standards and review practices for the team; mentor Senior and mid-level engineers; unblock the hardest cross-cutting technical problems.
• Innovation: Drive technical innovation through research, prototyping, and open-source contributions where relevant.

Required Skills and Qualifications:

• Bachelor's or Master's degree in Computer Science, Data Science, or a related field (PhD often preferred at this level).
• 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 and REST/gRPC APIs at scale.
• Expertise in frameworks like PyTorch, TensorFlow, Keras, or Scikit-learn.
• Solid understanding of containerization (Docker) and deployment environments (Kubernetes, cloud platforms); experience architecting for fault tolerance and reliability.
• Familiarity with MLOps best practices and cloud platforms such as AWS, Azure, or GCP.
• Solid understanding of data structures, algorithms, and software architecture.

Preferred Qualifications:

• Deep expertise designing complex AI systems from the ground up
• Experience architecting modern lakehouses (e.g., Delta Lake, Apache Iceberg) to process and manage massive, complex datasets specific to manufacturing, supply chain, or OT environments.
• Proven ability to optimize large language models for maximum throughput and low latency, with experience deploying AI into highly secure, on-premises, or edge environments.
• Strong familiarity with the broader AI lifecycle model i.e registries, vector/graph databases, LLM evaluation frameworks, agentic orchestration.

What Sets This Role Apart:

• The ability to lead large, complex projects from design through deployment, and to define the architecture that other engineers execute against.
• Experience with high-scale ML environments, distributed computing, and optimizing model inference latency.
• Proven ability to translate complex ML/systems concepts into business insights for stakeholders and leadership.

 

 

 

Learn more about us

 

 

 

• Impact 2025
• Cognite's Industrial AI: Moonshot
• We’re globally recognized domain experts with an international presence that spans Phoenix, Houston, Oslo Tokyo, Bengaluru, and Abu Dhabi.

 

 

Equal Opportunity

Cognite is committed to creating a diverse and inclusive environment at work and is proud to be an equal opportunity employer. All qualified applicants will receive the same level of consideration for employment.