Role Overview

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. This is not a traditional engineering role with long delivery cycles. You will be expected to go from concept to working prototype in days, not months, while maintaining enterprise-grade standards for quality, security, and scalability.

You bring a strong combination of skills: solution design and architecture experience, deep hands-on engineering across data and AI agents, and the interpersonal skills to earn trust, drive alignment, and collaborate effectively across teams. You are equally comfortable whiteboarding a system architecture with stakeholders and writing production code the same afternoon. You have genuine curiosity about the why and what behind every problem - not just the how - and you thrive in fast, ambiguous environments where creative thinking and execution speed both matter.

Key Responsibilities

Solution Design & Architecture
• 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

Rapid Prototyping & Solution Delivery
• Design and deliver working prototypes for complex data and AI problems within compressed timeframes, often days to weeks
• Bring genuine curiosity to every engagement - deeply understanding the business case, problem context, and constraints before converging on a solution
• Balance speed of delivery with enterprise standards - your prototypes are production-ready, not throwaway
• Continuously iterate on solutions based on direct feedback from product managers, program leads, and end users

AI Agent Development & Agentic Systems
• 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 LangChain, LangGraph, AutoGen, 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

AI & Data Engineering
• 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

Collaboration & Stakeholder Engagement
• 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

Qualifications

Required
• 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 connect agents with external systems
• Experience with agentic frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or Semantic Kernel
• Strong hands-on experience with data engineering: pipelines, ETL/ELT, data modeling, SQL and NoSQL databases
• Proficiency in Python
• Experience with cloud platforms (AWS, Azure, or GCP) and modern data stack tooling
• Exceptional communication and interpersonal skills - you can earn trust quickly, navigate ambiguity, and drive alignment across diverse teams
• Comfort working in fast-paced environments with shifting priorities and high ownership expectations

Preferred
• Experience with RAG architectures, vector databases (Pinecone, Weaviate, pgvector), and semantic search - including building end-to-end data pipelines that chunk, embed, and index unstructured content for retrieval
• Familiarity with prompt engineering, fine-tuning, and LLM evaluation techniques
• Experience with agent observability and tracing tools (LangSmith, Arize, Weights & Biases, or similar)
• Experience with AWS AgentCore - building, deploying, and operating agents on the platform
• Knowledge of data orchestration tools (Airflow, Prefect, or dbt)
• Experience with containerization and CI/CD practices (Docker, Kubernetes, GitHub Actions)
• Background in real estate, financial services, or other data-intensive enterprise domains
• Experience facilitating technical discovery workshops, design sprints, or architecture reviews
• Contributions to open-source agentic or data projects, or a portfolio demonstrating rapid, creative problem-solving

This position does not provide visa sponsorship. Candidates must be authorized to work in the United States without sponsorship.

Estimated compensation for this position:

140,000.00 - 180,000.00 USD per year

This range is an estimate and actual compensation may differ. Final compensation packages are determined by various considerations including but not limited to candidate qualifications, location, market conditions, and internal considerations.

Location:

On-site -Chicago, IL, Westmont, IL

If this job description resonates with you, we encourage you to apply, even if you don't meet all the requirements. We're interested in getting to know you and what you bring to the table!

Personalized benefits that support personal well-being and growth:

JLL recognizes the impact that the workplace can have on your wellness, so we offer a supportive culture and comprehensive benefits package that prioritizes mental, physical and emotional health. Some of these benefits may include:

• 401(k) plan with matching company contributions
• Comprehensive Medical, Dental & Vision Care
• Paid parental leave at 100% of salary
• Paid Time Off and Company Holidays
• Early access to earned wages through Daily Pay

At JLL, we harness the power of artificial intelligence (AI) to efficiently accelerate meaningful connections between candidates and opportunities. Using AI capabilities, we analyze your application for relevant skills, experiences, and qualifications to generate valuable insights about how your unique profile aligns with the specific requirements of the role you're pursuing.