Staff Software Engineer

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.
What This Job Involves
We're seeking an expert Staff Software Developer to architect end-to-end platform solutions, lead the adoption of agentic AI and LLM-powered capabilities across the platform, and bring deep experience building microservices and event-driven architectures at scale. This is a senior individual-contributor role with 10+ years of experience across multiple technology domains, a track record of shaping technical strategy rather than just executing against it, and a genuine drive to simplify the developer experience for the engineers around you.
What You'll Get To Do
As a Staff Software Developer, you will have ownership over the architecture and technical direction of platform-wide services and APIs, with AI-powered capabilities as a first-class part of that architecture. Your customers are every engineering team at JLL Technologies that consumes the platform's shared services they depend on the standards, APIs, and reusable frameworks you build to move faster and build reliably.
Your mission is to turn the platform into a force multiplier for every team that builds on it. This is an opportunity to shape how JLL Technologies architects cloud-native, AI-enabled software at enterprise scale, to simplify how other engineers build and ship, and to mentor the next generation of senior engineers along the way.
Key Responsibilities
Platform Architecture: 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.
Microservices & Event-Driven Systems: Design, build, and operate microservices and event-driven architectures that scale reliably, and evolve them as usage and team count grow.
APIs & Developer Experience: 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.
Cloud-Native Engineering: Architect and modernize services on Azure and/or AWS, partnering with cloud/DevOps engineering on reliability and cost.
Agentic AI & LLM Integration: 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.
Mentorship & Technical Leadership: 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.
Mentorship & Technical Leadership: 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.
Who You Are
You shape and define technical strategy rather than waiting for it to be handed to you, and you're equally comfortable writing production code and influencing an architecture decision across three teams. You're a forward-deployed thinker who evaluates new technology, agentic AI included, on its actual platform value, and you bring the credibility to get other senior engineers to follow your lead. You genuinely enjoy mentoring, you'd rather grow another engineer's judgment than just hand them the answer, and you measure a good week partly by how much simpler you made someone else's job. You default to building things that outlast the project they were built for.
Qualifications And Skills
Required Qualifications
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
Preferred Qualifications
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)
Key attributes
Strategic Thinking: Sees around corners on architecture decisions and plans for scale before it's required.
Thought Leadership: Shapes how other engineers think about platform architecture, not just how they build it.
AI Fluency: Uses AI coding tools with judgment, knows where they accelerate work and where they add risk ,and helps the team build the same skill.
Mentorship: Invests real time growing other engineers' skills and judgment, not just reviewing their work.
Developer Experience Focus: Treats other engineers as customers — simplifies their workflows and writes documentation clear enough that they rarely need to ask.
Ownership & Drive: Drives platform-wide initiatives to completion across team boundaries.
Collaboration: Partners across pillars to align platform direction with what teams actually need.
Communication: Translates deep technical trade-offs into decisions stakeholders can act on.

Work arrangement
Yes