We're hiring an experienced engineer to build the internal AI platform and systems layer for an established enterprise data security company with 40 years in the market. This is a hands-on role for someone who turns real-world workflows into robust internal systems. You'll partner with leadership, domain owners, and a knowledge engineer already deep in workflow design, process mapping, and eval design. The goal: understand how work actually happens, find where AI creates leverage, and build the infrastructure that makes it reliable. A core part of the work is building the connective layer across tools, workflows, documents, and operational signals that gives AI systems the context they need. You'll own what sits underneath: connectors, tool contracts, permissions, tracing, context services, deployment plumbing, and the applications on top. What you'd build: Process-mining agents that map how teams actually work Sandbox environments for testing AI systems against real operational data before rollout Orchestration and control-plane infrastructure for AI across functions Internal tools that close the gap between a working prototype and something a team can rely on daily
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Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed