Lead AI Engineer

Job Description At Thomson Reuters™, we’re transforming Service Management from a reactive, process-bound group into an AI-native, intelligence-driven organization. Operational data flows into intelligence, intelligence into orchestration, and orchestration into execution, in a closed loop with AI embedded in detection, decision, and action. Our AI Operations and Automation (AIOps) function is the intelligence layer of that model. Intelligence only matters if people can see it, question it, and act on it.

As more of our operations run through AI agents, the layer where people and agents meet the data decides whether any of it gets trusted. You’ll build that layer.

• Build dynamic data visualization. Design and engineer interactive, real-time views of operational data, including topology and dependency graphs, event and alert streams, incident timelines, and predictive signal. Think D3, WebGL, and modern front end, not drag-and-drop BI.
• Define the agent-to-agent interface. Establish the interfaces and data contracts that let AI agents pass structured, verifiable information to one another, and hand it to engineers in a form they can inspect and challenge.
• Make automated action visible. Our L0 tier is where AI and automation resolve issues ahead of human responders. Show what it did, why, and how confident it was, so engineers supervise machine decisions rather than simply receive them.
• Design the experience. Lead the UI/UX and information architecture: research how responders work under pressure, decide what they need to see and when, shape the interaction model, and make a complex system feel simple to someone working an incident at 3 am.
• Prototype and ship. Turn ambiguous problems into working software quickly, then harden the strongest ideas into tools our teams depend on.
• Set technical direction. As a lead, you’ll set the standard for the experience layer, make the architectural calls, and mentor engineers and designers. A builder first, a coach alongside.
• Partner closely. Work day to day with AIOps, Service Data and Insights, Configuration and Topology, Workflow Engineering, and the Global Command Center.

• Replace an operational report our teams read line by line with an interactive view that answers the question in seconds.
• Publish the first version of our agent-to-agent data contract, and prove it with two agents working together in production.
• Ship the interface that lets engineers see, and trust, every L0 resolution they’re accountable for.
• Establish the shared patterns the rest of the organization builds on: components, guidelines, and working prototypes.

• Experience. 8+ years designing and building software, including data-rich, user-facing products, hands-on applied AI or agentic work, and time setting technical direction for others. A degree in computer science, human-computer interaction, design, or a related field, or equivalent experience.
• A hybrid background. Deep experience in two of these three and fluency in the third: front-end and data-visualization engineering, applied AI, and UI/UX design.
• Information architecture and user-centric design. You structure dense information so people find what matters without hunting for it, and you ground design decisions in research with real users, including interviews, task analysis, and usability testing.
• Dynamic visualization in production. You’ve shipped interactive data visualization in JavaScript or Type Script, with React and tools such as D3.js, WebGL, or Canvas, and you care how it feels as much as whether it renders.
• Applied AI fluency. Hands-on with large language models and agentic systems, including tool calling, retrieval, and emerging agent interoperability…