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Bengaluru, Karnataka, India
Hybrid
Cognite operates at the forefront of industrial digitalization, building AI, and data solutions that solve the world’s hardest, highest-impact problems. With unmatched industrial heritage and a comprehensive suite of AI capabilities, including low-code AI agents, Cognite accelerates the digital transformation to drive operational improvements.
We thrive in challenges. We challenge assumptions. We execute with speed and ownership. If you view obstacles as signals to step forward - not backwards - you’ll feel right at home here.
Our Moonshot is bold: Unlock $100B in customer value by 2035, and redefine how global industry works. Join us in this venture where AI and data meet ingenuity, and together, we will forge the path to a smarter, more connected industrial future.
As a Senior AI Agent Engineer, you will be the primary owner and architect for building, enhancing and maintaining a packaged , customer ready solution of agentic workflows geared to integrated supply chain pumping the heart of industrial digital transformation.
You are not just building models, you are building agents capable of traversing the Cognite Data Fusion (CDF) Knowledge Graph to automate complex supply chain decisions.
You will be part of the CoE team working closely with our global customers across industries, and integrating and scaling the packaged agents in their daily operations. You will lead discovery workshops, and reimagine and define new ways of working with agents as co- workers. You will incorporate new learning, usable across customers, in the packaged agent offering.
Use Cognite Flows to enable workflows for visibility, exception surfacing, root cause analysis and recommendations. Also work with partners to enable end to end workflows for adaptive planning and action.
You will work with a data model that integrates Maintenance Execution (Work Orders), Production Planning (Batches/Recipes), Inventory & Inbound/Outbound Logistics, (Shipments/Deliveries), suppliers & customers and external market & risk data. The agents will need to "reason" across these domains.
The role will require deep collaboration with sales, product , value delivery and partners.
- with product, to ensure alignment with product standards and quality. Make it product-ready
- with Value Delivery, to support during initial rollouts or pilot deployments, providing technical depth where needed and helping troubleshoot agent behaviour in context and develop a feedback process, in order to improve use case / agent readiness and alignment with customer expectations
- with Field Engineering, in scoping and qualifying AI agent use cases — helping assess technical feasibility, data readiness, and fit between customer environments and packaged agent assumptions. Also, gathering structured feedback from pre-sales interactions on common customer objections, technical concerns, and unmet requirements — and feeding these signals back into agent design and packaging priorities
- with a partner ecosystem, to develop/ enhance the agentic solutions for pilot customers, and close loop feedback from partners feeding into agent design and enhancements.
