Senior GIS Engineer

JLL•Chicago, IL

5d•$147,000 - $278,000•Remote

About The Position

The Senior Software Engineer develops, tests, documents, and maintains robust, scalable full stack applications using modern technologies including AI, cloud platforms, GIS, and DevSecOps practices. This role works across JLL’s geospatial and enterprise data platforms on problems such as geocoding, data matching, and cross-platform data alignment.

Requirements

5+ years of professional software engineering experience with full stack expertise — frontend (React, modern JavaScript) and backend (C#, .NET)
Geospatial: GIS data processing, mapping libraries and platforms, spatial databases, and location-based services
Geocoding & matching: Hands-on experience with geocoding frameworks (address standardization, composite geocoding, coordinate-based matching) or with record matching and deduplication at scale
Data integration: Defining data contracts, identifier mappings, and integration patterns across platforms; relational and NoSQL databases
AI/ML: Integrating AI capabilities into solutions; familiarity with LLMs (prompt engineering, API integration); proficiency with AI coding assistants to accelerate development
Cloud & DevSecOps: A major cloud platform (AWS, Azure, or GCP), E2E CI/CD setup, and automated testing practices
Works independently on complex problems and builds alignment across teams without formal authority

Nice To Haves

Production experience with large-scale data matching and deduplication, or with shared geocoding services
Familiarity with property, building, or location identity concepts (building identifiers, address hierarchies, parcel/structure relationships)
Deep knowledge of spatial analysis and cartographic principles
Experience with Databricks or similar lakehouse platforms for large-scale geospatial data processing
Experience building LLM-powered applications (RAG, vector search) or deploying ML models in production
Knowledge of real estate technology and JLL’s technology ecosystem
Familiarity with responsible AI practices; professional certifications in cloud, GIS, or AI/ML

Responsibilities

Independently design and implement complex solutions — geospatial data pipelines, geocoding and matching services, and the interfaces between them — with testing, monitoring, and data-quality validation built in
Solve medium to high complexity problems, including reconciling records across systems with differing identifiers and data models
Bring new perspectives to existing solutions, applying AI and automation to improve both products and development practices
Work with product and business teams to influence solution decisions, translating business needs into technical requirements
Apply enterprise-first thinking: contribute & build shared capabilities and data contracts that serve multiple platforms and teams
Lead medium projects with manageable risks and serve as a trusted opinion in your product area
Coach less experienced engineers and deliver knowledge-sharing sessions
Use storytelling to explain difficult concepts and build consensus across platform teams and business stakeholders