Staff Forward Deployed Engineer

JLL empowers you to shape a brighter way. Our people at JLL are shaping the future of real estate for a better world by combining world class services, advisory and technology for our clients. We are committed to hiring the best, most talented people and empowering them to thrive, grow meaningful careers and to find a place where they belong. Whether you’ve got deep experience in commercial real estate, skilled trades or technology, or you’re looking to apply your relevant experience to a new industry, join our team as we help shape a brighter way forward. Role Overview As a Staff Forward Deployed Engineer, you will operate at the front lines of innovation — embedded directly with multiple cross-functional teams to rapidly design, architect, prototype, and deploy solutions that solve their highest-priority problems. This is not a traditional engineering role with long delivery cycles: you will be expected to go from concept to working prototype in days, not months, while maintaining enterprise-grade standards for quality, security, and scalability. You will act as the embedded technical owner across several teams simultaneously — diagnosing their workflow and data problems, then architecting and building the fix yourself. You will use modern AI coding assistants day-to-day to design and implement solutions, and you're expected to be fluent extending that toolset — building [... source excerpt omitted ...] ive alignment, and influence without authority across multiple teams at once. You are equally comfortable whiteboarding a system architecture with senior stakeholders and shipping production code the same afternoon. Key Responsibilities Solution Design & Architecture Lead solution design for complex, cross-functional data and AI problems — from initial discovery through to technical blueprint Evaluate and select the right tools and architecture for each problem — no single stack applies across every team you support, so you must be able to reason across different platforms, data sources, and integration patterns Define and communicate architecture decisions, trade-offs, and de [... source excerpt omitted ...] opt across engagements AI-Assisted Solution Delivery Use AI coding assistants as your primary development environment for day-to-day solution building — from prototyping through production implementation Build and maintain custom plugins/skills for your AI coding assistant that package reusable capabilities for recurring problems across teams Redesign and rebuild data pipelines and data flows to unblock use cases — including source integration, transformation logic, and downstream delivery Deploy and operate AI agents in production via AWS Bedrock AgentCore Translate ambiguous business requirements from stakeholders into concrete technical solutions with minimal hand-holding