Staff Software Engineer

Job Summary

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.

What this job involves:

JLL REMS (Real Estate Management Services) is building next-generation AI-powered solutions to transform how our clients interact with and derive insights from property management data. We are seeking a talented Staff Software Engineer who combines deep AI expertise with full-stack development capabilities to architect, build, and lead the development of features for one of our flagship Commercial Real Estate (CRE) products.

As a Staff Software Engineer, you will design, develop, and deploy end-to-end GenAI solutions that enable users to retrieve knowledge, analyse information through intuitive interfaces. You will be responsible for building intelligent backend systems that translate natural language into actionable queries, as well as creating user-facing interfaces that deliver AI-powered insights. You will be mentoring junior and mid-level engineers, driving architectural decisions, establishing technical standards, and ensure code quality through comprehensive automated testing strategies.

Responsibilities

Collaboration Delivery

• Collaborate with product managers, cross-functional teams, and business stakeholders, to gather requirements and define project scope
• Translate business requirements into technical specifications and architectural designs
• Lead the design and implementation of complex features across the full stack and contribute to strategic planning
• Mentor and provide technical guidance to junior and mid-level developers in integrating and utilizing AI-powered solutions effectively
• Conduct code reviews and address bugs, performance issues, and technical debt
• Work effectively in an Agile/Scrum environment to ensure timely and successful delivery
• Drive architectural decisions and establish technical standards for both front end and back-end systems
• Lead refactoring initiatives to improve system architecture and reduce technical debt
• Lead troubleshooting efforts for complex issues across the entire technology stack
• Participate in on-call rotation and lead incident response when needed

AI development

• Research and develop state-of-the-art GenAI-based solutions for property management applications
• Build and optimize RAG (Retrieval-Augmented Generation) pipelines using LLMs to efficiently utilize property management data from data warehouses and semantic indexes
• Implement AI based techniques to extract valuable insights and patterns from data, enabling actionable recommendations and predictions
• Design and develop agentic AI systems and implement Model Context Protocols (MCPs) for enhanced AI capabilities
• Develop and fine-tune GenAI workflows for complex decision-making scenarios.
• Establish best practices for using AI tools like Claude to enhance team productivity

Full Stack Development

• Develop and implement robust web applications using React, Python, Django, and the Django REST Framework
• Design and develop efficient, scalable backend applications and APIs that integrate seamlessly with AI models
• Create responsive and intuitive front-end interfaces using React / NextJS, HTML5, CSS3, and JavaScript
• Establish and enforce secure coding standards / practices, patterns, and project structure guidelines across the full stack
• Design comprehensive testing strategies and write sophisticated unit and integration tests for both front end and back-end components
• Own deployment procedures and creating runbooks for full stack releases

Cloud Infrastructure DevOps

• Design and implement Infrastructure as Code (IaC) using Terraform for scalable cloud deployments.
• Deploy and manage AI services on cloud platforms, including Azure Search Service and OpenSearch.
• Build and maintain CI/CD pipelines using GitHub Actions and other automation tools.
• Ensure scalability, performance, and reliability through regular testing, debugging, and optimization.
• Implement containerization using Docker and orchestration for microservices architectures.

Continuous Innovation

• Keep up to date with the latest advancements in GenAI technologies, LLMs, and agentic AI frameworks.
• Continuously improve software development processes and practices.
• Stay current with emerging cloud technologies, DevOps practices, and full-stack development trends.

Experience and Education

Required

• Bachelors degree or higher in Computer Science, AI, Engineering, or a related field
• 7+ years of proven experience as a Full Stack Developer, AI Engineer, or similar role with a proven track record of mentoring engineers and fostering technical growth within teams
• Strong proficiency in Python and relevant AI libraries and frameworks (LangChain, Langgraph etc.)
• Demonstrated experience developing GenAI-based solutions and tools using LLMs
• In-depth knowledge of Natural Language Processing (NLP) techniques, including language models, RAG pipelines, and text generation algorithms
• Strong proficiency in full-stack development with React / NextJS, Python, Django, and Django REST Framework
• Experience with front-end technologies: HTML5, CSS3, JavaScript, and modern React patterns.
• Strong knowledge of SQL and database technologies (PostgreSQL, MySQL).
• Hands-on experience building and maintaining CI/CD pipelines (GitHub Actions, Azure DevOps, etc.)
• Proven experience with Infrastructure as Code (IaC) using Terraform
• Experience with cloud computing platforms (AWS or Azure) and their AI services
• Familiarity with Azure Search Service and/or OpenSearch for semantic search implementations
• Experience with containerization technologies (Docker) and distributed computing architectures
• Understanding of Agile/Scrum methodologies and software development lifecycle

Preferred

• Experience developing agentic AI systems and implementing Model Context Protocols (MCPs).
• Familiarity with vector databases and semantic indexing technologies.
• Experience with API gateway design and microservices architectures.
• Knowledge of security best practices for AI systems and data privacy compliance.
• Experience with monitoring, observability, and performance optimization tools like DataDog

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.