Senior Data Engineer

Westmont, IL 60559

JLL is a leading professional services firm that specializes in real estate and investment management. The Data Engineering team sits at the intersection of technology and business impact, building the data foundations and intelligent solutions that power decisions across the enterprise.

As a Forward Deployed Data Engineer, you will be embedded directly with product, program, and engineering teams to design, architect, prototype, and deploy data‑driven solutions that solve high‑priority business problems. You will move from concept to working prototype in days, while maintaining enterprise‑grade standards for quality, security, and scalability.

• Drive 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 and Critical Design Reviews (CDRs), ensuring alignment with enterprise patterns and platform standards.
• Create clear technical documentation: architecture diagrams, data flow maps, API contracts, and solution briefs.

• Design and deliver working prototypes for complex data and AI problems within compressed time frames, often days to weeks.
• Deeply understand the business case, problem context, and constraints before converging on a solution.
• Balance speed of delivery with enterprise standards—prototypes are production‑ready, not throwaway.
• Continuously iterate on solutions based on direct feedback from product managers, program leads, and end users.

• 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 MCP (Model Context Protocol) servers and clients to connect AI agents with enterprise tools, APIs, and data sources.
• Build agent orchestration layers using frameworks such as Lang Chain, Lang Graph, Auto Gen, CrewAI, or Semantic Kernel.
• 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.

• Build and deploy AI‑powered features and pipelines that automate workflows, surface insights, and enhance decision‑making.
• Design and implement scalable data pipelines, APIs, and backend services that serve both internal tools and customer‑facing products.
• Integrate LLMs, RAG systems, and ML models into production data workflows.
• Own data modeling, transformation, and quality across the solutions you deliver.

• Embed directly with product, program, and engineering teams to co‑define problems and co‑deliver solutions.
• Contribute to technical direction and help build alignment across teams through strong communication and collaboration.
• Communicate complex technical concepts clearly to non‑technical business stakeholders— in writing, in meetings, and in presentations.
• Support and mentor junior engineers, sharing patterns and practices for agentic development, prompt design, and rapid delivery.
• Foster a collaborative, low‑ego team culture where speed and quality go hand in hand.

• 4+ years of professional software or data engineering experience, including hands‑on solution design and architecture contributions.
• Experience designing and delivering end‑to‑end data and AI systems—from requirements through deployment—with clear documentation and stakeholder communication.
• Hands‑on experience building AI agents, including defining agent skills, tool use, memory, and multi‑step reasoning.
• Working knowledge of MCP (Model Context Protocol)—including building or consuming MCP servers to…