Staff Software Engineer

JLL•Chicago, CO

9h•Remote

About The Position

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. About JLL and JLL Technologies JLL is a leading professional services firm that specializes in real estate and investment management. Our vision is to reimagine the world of real estate, creating rewarding opportunities and amazing spaces where people can achieve their ambitions. In doing so, we will build a better tomorrow for our clients, our people, and our communities. At JLL Technologies, our mission is to bring technological innovation to commercial real estate. We deliver unparalleled digital advisory, implementation, and services solutions to organizations globally. Our goal is to leverage technology to increase the value and liquidity of the world's buildings, while enhancing the productivity and happiness of those that occupy them. JLL Technologies' Enterprise Data Platform (EDP) Platform Engineering team builds the shared services, APIs, and ingestion frameworks that every data and product team at JLL Technologies builds on top of. We're just getting started on reshaping the business of commercial real estate with the power of data and this team is the foundation that makes it possible.

Requirements

10+ years of professional software engineering experience, including architecting complex, end-to-end platform solutions across multiple technology domains
Strong command of object-oriented programming and design patterns, including domain-driven design (DDD), event-driven architecture, and microservices
Proficiency in at least one backend language - Java, C#, or Python
Proven full-stack experience end-to-end, designing and building RESTful APIs from the data layer through to the services that consume them
Hands-on experience building AI-powered features (LLMs, AI agents) and using AI coding tools such as Claude Code, GitHub Copilot, or Cursor responsibly to accelerate your own development work
Deep, hands-on experience with cloud-native architecture on Azure and/or AWS
Track record of simplifying how other engineers work and writing clear, accessible documentation for what you build
Strong communication skills, with the ability to explain technical trade-offs to both engineers and business stakeholders
Candidates must be authorized to work in the United States without sponsorship.

Nice To Haves

Front-end experience with TypeScript/JavaScript and a modern framework (React or Angular) for building user-facing web applications
Experience with MCP-based tooling or building agentic AI systems that other engineering teams consume
Hands-on experience with agent harness engineering and spec-driven development, and a habit of tracking emerging AI coding techniques and sharing what works with the team
Familiarity with additional API paradigms beyond REST, such as GraphQL or gRPC
Cloud certifications (Azure Solutions Architect, AWS Solutions Architect, or equivalent)

Responsibilities

Architect and build end-to-end platform solutions, backend services, RESTful APIs, and front-end interfaces where needed, applying OOP, DDD, and event-driven patterns so they stay maintainable as they scale.
Design, build, and operate microservices and event-driven architectures that scale reliably, and evolve them as usage and team count grow.
Own the platform's core APIs built on RESTful principles — and shared frameworks, simplifying how other engineering teams build on them and backing every service with documentation clear enough that teams rarely need to ask.
Architect and modernize services on Azure and/or AWS, partnering with cloud/DevOps engineering on reliability and cost.
Lead the integration of agentic AI, LLM, and MCP-based capabilities into platform services, stay fluent in fast-moving AI coding tools (Claude Code, GitHub Copilot, Cursor, and similar), and set team guidelines for where AI-assisted development helps versus where it adds risk.
Mentor senior and lead engineers including on responsible AI tool use influence technical direction across teams, and act as the go-to expert for platform architecture decisions.