Industrial · Industrial DataOps
Currently tracking 11 active AI roles, down 15% versus the prior 4 weeks. Primary focus: Agent · Engineering.
Cognite currently has 24 active job listings related to artificial intelligence. The majority of these roles are focused on the application stage, accounting for 33% of the openings, followed closely by agents at 29% and data at 25%. Engineering is the primary function for these hires, with a significant concentration of roles in India, followed by Norway. The company is actively seeking candidates with experience in agent orchestration, retrieval-augmented generation (RAG), and LLM observability. Over the last 30 days, Cognite has significantly increased its AI hiring, with 25 new roles posted, representing a 213% increase compared to the previous 30-day period.
Cognite currently has 20 active AI-related roles in our index. The most common open titles are: Data Engineering Leader (3), Senior Solution Architect (3), Enterprise Architect (2), India Template (2), Principal Field Engineer (2). Most positions are in Engineering and Product.
Cognite's active AI hiring is concentrated in: application (40%), agents (25%), data (25%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Cognite is hiring AI talent in: India (7 roles), Norway (5 roles), United States (2 roles), Germany (2 roles).
Job postings at Cognite most frequently mention: Software Engineering, Mechatronics, Data Pipelines, CI/CD, Algorithms & Data Structures.
In the past 30 days, Cognite has posted 13 new AI-related roles. That is a -38% change versus the prior 30 days (21 → 13).
| Title | Stage | AI score |
|---|---|---|
| India Template This role is for a Principal Information Security Engineer in Bengaluru, India, focused on building and leading a security engineering team. A core responsibility is the aggressive implementation and orchestration of AI to automate and optimize SecOps detection pipelines and Product Security guardrails. The role involves designing AI-driven SecOps with agents for detection and response, and AI-accelerated Product Security with automated scanning and remediation guidance. It also includes threat modeling, hardening cloud environments, and technical leadership for team building and regional security initiatives. | AgentServe | 8 |
| Senior AI Engineer - Supply Chain Senior AI Engineer focused on building and enhancing packaged, customer-ready agentic workflows for supply chain automation. The role involves developing multi-agent systems that leverage tool-use, memory, and reasoning to interact with a knowledge graph, automate complex decisions, and provide operational insights and recommendations. Requires strong full-stack engineering skills, experience with LLM-driven agent frameworks, and understanding of industrial and supply chain data. |
| Agent |
| 8 |
| Applied AI Engineer Applied AI Engineer role focused on designing and building AI-powered solutions, including agentic systems and user-facing applications, for industrial digitalization. The role involves end-to-end ownership of deployments, integration with existing systems, and collaboration with customers and product teams. | Agent | 8 |
| Principal ML Engineer Principal ML Engineer to design, build, and deploy scalable ML systems for industrial digitalization, focusing on transforming unstructured data into actionable intelligence using Deep Learning, Generative AI, and Computer Vision. The role involves engineering production-grade code, optimizing inference, and integrating AI into existing systems, with a focus on scaling and real-time applications. | ServeAgent | 8 |
| Senior Machine Learning Engineer Senior Machine Learning Engineer role focused on building and deploying AI/ML models for industrial digitalization. The role involves designing, training, testing, and deploying models for document parsing, layout analysis, and entity matching, with a strong emphasis on production-grade code, robust APIs, and scalable infrastructure. Responsibilities include building ML models as software components, implementing CI/CD pipelines, optimizing inference, and monitoring deployed models. Experience with NLP, Vision-Language Models, MLOps, and cloud platforms is required. | AgentServe | 8 |
| Senior Software Engineer - ( Context Services ) Senior Software Engineer to lead production systems for Context Services, bridging Applied Scientists/AI Engineers and Platform Engineering. Focus on turning analytical solutions (ML/DL models, LLM agents) into reliable, production-grade software services. Key responsibilities include designing scalable APIs, architecting frameworks for model serving, vector databases, and agentic workflows, and integrating with central platform teams. | AgentServe | 7 |
| India Template Senior Engineer to lead production systems for Context Services, bridging Applied Scientists/AI Engineers and Platform Engineering. Focus on turning analytical solutions (ML/DL models, LLM agents) into reliable, production-grade software services. Design architectures for low-latency APIs, collaborate on industrial data problems, architect frameworks for model serving, vector databases, and agentic workflows, and act as a liaison with the central Platform team. | AgentServe | 7 |
| India Template Software Engineer to join the Context Services team, focusing on transitioning AI/ML models and LLM agents from experimentation to scalable production. Responsibilities include developing low-latency APIs, building automated pipelines for deployment and monitoring, and ensuring system health for industrial AI solutions. | ServeAgent | 7 |
| Machine Learning Engineer Machine Learning Engineer role focused on building and deploying AI models and pipelines for industrial digitalization. The role involves data processing, fine-tuning foundational models (NLP, Vision-Language), creating APIs for ML capabilities, and ensuring production-grade code quality and system design. | ServePost-train | 7 |
| Senior Principal Architect Senior Principal Architect role focused on designing and evolving the data integration architecture for industrial digitalization and AI solutions. The role involves leveraging generative AI, architecting foundational services, and ensuring scalability and cost-efficiency, with a specific emphasis on enabling AI agents within data pipelines. | AgentData | 7 |