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 the Role
As a Software Engineer I on the Martech Intelligence Pod, you'll be starting your engineering career working on real customer-facing applications across both frontend and backend, learning the foundations of professional software development in a supportive environment. You'll also have the opportunity to explore and learn about AI tools and AI-centric solutions that are becoming central to how we build products.
Your primary focus will be maintaining and improving the customer-facing websites we host while gradually learning about infrastructure and integration challenges the Intelligence Pod tackles. Importantly, you'll also have dedicated time to explore AI tools, experiment with LLM APIs, understand how agents work, and think about where AI can solve problems better than traditional approaches.
This is a structured onboarding role: you'll work closely with senior engineers who will mentor you through the full development lifecycle — from understanding requirements, to writing frontend components and backend services, to testing, debugging, and deploying to production. You'll start with well-scoped, low-risk tasks on both frontend and backend, and gradually take on more responsibility as you gain confidence and expertise. You'll also spend time experimenting with AI tools, building small proof-of-concepts, and learning how modern AI capabilities can be integrated into applications.
The role demands intellectual curiosity, a willingness to ask questions, and genuine interest in learning how real systems work — both traditional software and AI-powered systems. Success is measured by your growth as a full-stack engineer, the quality of code you write, your reliability, your ability to communicate what you're learning, and your engagement with exploring AI as a tool and mindset. This is a fully-supported entry point into professional full-stack software engineering at a global scale, with exposure to cutting-edge AI capabilities.
Who You Are
We're optimizing for learning potential, solid fundamentals, and genuine engagement with engineering. You don't need years of experience — you need to be curious, humble about what you don't know, and eager to grow.
- You have a Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent bootcamp/self-taught experience with a portfolio demonstrating competency
- You are proficient in English, both written and verbal, sufficient for success in a remote and largely asynchronous work environment
- You have 0-2 years of professional software engineering experience, or are a recent graduate with solid foundational knowledge
- You have hands-on experience writing code in C# or Java (through academic projects, bootcamp, or personal projects) and understand the basics of how programs work
- You have some experience with React and TypeScript or are eager to learn them quickly — through academic projects, bootcamp, tutorials, or personal projects; you understand the basics of components and JSX
- You know the basics of HTML, CSS, and JavaScript — you understand how the browser works and can build simple web pages and interactive elements
- You understand the fundamentals of object-oriented programming: classes, objects, inheritance, and interfaces
- You can debug code in multiple environments: backend (logs, IDE debugger) and frontend (browser developer tools, console logs)
- You've written code that other people have read and reviewed — you're comfortable receiving feedback and iterating
- You know the basics of relational databases and can write simple SQL queries (SELECT, INSERT, UPDATE); you're learning to think about data
- You've worked with Git and understand the basics of version control, branching, and merging
- You can debug code systematically: read error messages, add logging, trace through code, form hypotheses about what's wrong
- You're genuinely curious about how things work and you ask good questions when you don't understand something
- You're interested in and curious about AI tools (LLMs, generative AI, agents) — you've probably experimented with ChatGPT, Claude, or similar tools and think about how they could be useful
- You're open to exploring AI-centric solutions to problems and willing to experiment with new approaches that leverage AI capabilities
- You can explain what you've learned in writing: you're comfortable documenting decisions, asking for help in PRs, and sharing what you discovered
- You're reliable and follow through: you finish what you start, communicate when you're blocked, and ask for help before getting stuck for too long
- You're humble about what you don't know and genuinely want to learn from more experienced engineers
- You make an effort to include others and appreciate feedback as a gift, not a criticism
What You'll Do
Learning & Foundational Work:
- Work on small, well-scoped tasks with clear acceptance criteria: bug fixes, simple feature additions, documentation improvements (both frontend and backend)
- Get hands-on with the tools and technologies we use: C#/Java backend, React/TypeScript frontend, SQL, Git, our test frameworks, our deployment processes
- Learn how our customer-facing applications work: what AEM is, how WordPress sites are structured, how they serve customers, how frontend and backend work together
- Understand the full development lifecycle: from understanding a requirement, to writing code (frontend components and backend services), to testing, to deploying to production with safety
Frontend Development:
- Fix simple bugs in our React/TypeScript applications: layout issues, component state problems, missing features
- Implement small features: simple forms, content displays, UI improvements requested by stakeholders
- Learn React fundamentals: components, hooks, props, state management
- Debug frontend issues using browser developer tools: understand CSS problems, trace JavaScript execution
- Help improve frontend test coverage: write simple unit tests for components
- Learn how to consume backend APIs from the frontend: understand requests, responses, error handling
Backend Development:
- Help fix bugs in our C# or Java backend services: simple issues with clear reproduction steps
- Implement small backend features: API endpoints, database queries, business logic
- Learn backend fundamentals: how services are structured, how databases work, how to handle errors
- Debug backend issues: read logs, understand stack traces, trace through code
- Help improve test coverage: write simple unit and integration tests
- Learn how different systems connect: understand what the Intelligence Pod builds
Customer-Facing Site Support:
- Help maintain and support http://jll.com (AEM) and WordPress installations — responding to issues, fixing bugs, implementing small improvements
- Participate in code review: both receiving feedback on your code and reviewing code from peers (with guidance)
- Help with code maintenance: refactoring simple code, improving documentation, reducing technical debt
Learning Infrastructure & Integration Concepts:
- Observe and help with integration work: understand how we connect to external systems, why these connections are fragile, how errors are handled
- Learn what the broader Intelligence Pod does: building MCPs, working with agents, connecting marketing systems together
- Ask questions and document what you learn: you're building your mental model of how these systems work
AI Exploration & Learning:
- Dedicate time to learning and experimenting with AI tools: LLM APIs (Claude, GPT, etc.), prompt engineering, understanding how agents work
- Build small personal projects and proof-of-concepts using AI: tools that solve real problems, experiments that help you understand AI capabilities and limitations
- Explore how AI can be integrated into our applications: think about where AI could improve user experience, automate tasks, or unlock new capabilities
- Learn about agent systems, multi-step reasoning, and tool use: understand what the Intelligence Pod is building and why
- Document your experiments and learnings: write up what you tried, what worked, what didn't, and what you discovered
- Participate in code reviews and discussions about AI-centric solutions: understand how senior engineers think about AI architecture and tradeoffs
- Stay current on AI developments: follow announcements, experiment with new models/tools, and bring ideas back to the team
Development Practices: