Staff Software 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.   

Forward Deployed Engineer
Capital Markets Technology · JLL

About JLL

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 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 Forward Deployed Engineer, you will operate at the front lines of innovation — embedded directly with subject matter experts, product, and engineering teams to rapidly design, architect, prototype, and deploy solutions that solve high-priority business 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 bring an exceptional combination of skills: deep hands-on engineering experience across AI agents and full-stack development, and the interpersonal skills to earn trust, drive alignment, and influence without authority. You are equally comfortable whiteboarding a system architecture with senior stakeholders and writing production code the same afternoon. You thrive in fast, ambiguous environments where creative thinking and execution speed matter, and you're also a dependable partner when production systems need attention.

Key Responsibilities

Solution Design & Architecture

• Lead solution design for complex, cross-functional data and AI problems — from initial discovery through to technical blueprint
• Define and communicate architecture decisions, trade-offs, and delivery approaches to both technical and non-technical audiences
• Design scalable, modular systems that balance the need for speed with enterprise standards for reliability, security, and maintainability
• Participate in architecture reviews, ensuring alignment with enterprise patterns and platform standards
• Create clear technical documentation: architecture diagrams, data flow maps, API contracts, and solution briefs

Rapid Prototyping & Solution Delivery

• Design and deliver working prototypes for complex data and AI problems within compressed timeframes, often days to weeks
• Translate ambiguous business requirements into concrete technical solutions with minimal hand-holding
• Balance speed of delivery with enterprise standards — your prototypes are production-ready, not throwaway
• Continuously iterate on solutions based on direct feedback from product managers, program leads, and end users
• Develop intuitive front-end interfaces and dashboards that bring data and AI outputs to life for business users

AI Agent Development

• Design, build, and deploy AI agents and multi-agent systems that automate complex workflows end-to-end
• Develop and maintain agent skills — discrete, reusable capabilities that compose into larger agentic pipelines
• Implement and extend Model Context Protocol (MCP) servers and clients to connect AI agents with enterprise tools, APIs, and data sources
• Design evaluation harnesses, guardrails, and monitoring pipelines to ensure agent reliability and safety in production
• Stay current with the rapidly evolving agentic AI landscape and proactively introduce new techniques and tooling to the team
• Integrate LLMs, RAG systems, and ML models into production workflows

Application Support & Operational Reliability

• Serve as a technical point of contact for production issues across deployed AI and data applications, triaging and resolving incidents promptly
• Monitor application health, respond to alerts, and coordinate with platform and infrastructure teams to maintain SLA commitments
• Contribute to post-incident reviews, identify root causes, and implement preventive measures to reduce recurrence
• Maintain runbooks and operational documentation so that support responsibilities are scalable and transferable across the team