Pauline Brunet is Cursor’s vice president of forward deployed engineering, leading teams that help enterprises integrate AI coding tools into their software, workflows, and business operations. Her work centers on forward deployed engineering: embedding experienced technical specialists with customers to solve specific organizational problems and deliver measurable returns.
From enterprise transformation to Cursor
Brunet studied business administration at Wilfrid Laurier University, qualified as a chartered professional accountant, and later earned a master’s degree in computer science from the University of Illinois Urbana-Champaign. Earlier roles included General Electric, PwC Canada, and Montreal-based Element AI, where she led multidisciplinary teams developing AI-powered software for enterprise customers. Her work there included applying optical character recognition to manual, information-heavy processes and examining how automation could shift accountants toward analysis and decision-making.
At Cursor, her teams work inside customer codebases, deploy long-running cloud agents, build automations, and develop applications with the Cursor SDK. Their projects can extend beyond software development into finance, supply chains, e-commerce, and customer operations.
Her approach to enterprise AI
Deploy engineers where they change the outcome. Brunet assesses customers according to their technical maturity and the customization a product requires. Straightforward deployments should rely on documentation and self-service; embedded engineers belong where configurable technology and organizational complexity demand hands-on collaboration.
Co-develop instead of supplying temporary staff. Projects require senior sponsorship, a well-defined business problem, named customer collaborators, and shared ownership. Customers participate in design, implementation, human-in-the-loop validation, and measuring results, ensuring systems remain useful after the engagement ends.
Define success in business terms. Brunet evaluates projects against revenue growth, cost reduction, or risk mitigation. Engagements can begin with an approximately six-week implementation window while remaining flexible enough to accommodate unfamiliar systems, changing requirements, and emerging customer needs.
Turn customer proximity into product intelligence. Embedded engineers identify new applications and platform limitations early, creating a feedback loop with product and engineering teams. Brunet hires experienced software engineers who can navigate customer organizations, communicate with executives and developers, and decline projects when the technology is unsuitable.
Her AI Engineer conference talk articulates a practical standard for enterprise adoption: AI succeeds when customers can identify the operational problem it solves, participate in building the solution, and demonstrate lasting business value.
