Senior GIS Engineer

JLL; Chicago (IL); On-site; USD 140,000 - 190,000; Full time

Job summary

JLL is seeking a Senior Software Engineer to design, build, and maintain scalable full-stack applications across geospatial and enterprise data platforms. The role focuses on geocoding, data matching, and cross-platform data alignment with AI and DevSecOps practices.

You will work with product teams to translate business needs into technical requirements and lead knowledge-sharing sessions while mentoring engineers.

Qualifications

• 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 or record matching 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 and API integration.
• Cloud & DevSecOps: A major cloud platform (AWS, Azure, or GCP), CI/CD, automated testing.

Responsibilities

• Independently design and implement complex geospatial data pipelines and services with testing, monitoring, and data-quality validation.
• Solve medium to high complexity problems, reconciling records across systems with differing identifiers and data models.
• Apply AI and automation to improve products and development practices.
• Work with product and business teams to translate needs into technical requirements and data contracts.

Skills

Full-stack development

React / JavaScript

C# / .NET

Geospatial data processing

AI / ML integration

Cloud & DevSecOps

Data integration

Geocoding & matching

Education

Bachelor's degree in computer science or related field

Tools

Databricks

GIS platforms

LLMs (prompt engineering)

AI coding assistants

Job description

Role Overview

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.

Role Overview

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.

Key Responsibilities

Design & Delivery

• 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

Business Partnership

• 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

Leadership & Communication

• 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

Required Qualifications

We don't expect any single candidate to arrive with every skill listed below. If you're strong on full stack development and have depth in either GIS or applied AI, we want to hear from you - the rest is learnable on the job.

Education

• Bachelor's degree in computer science, Software Engineering, Information Technology, Geography/GIS, or related field; equivalent practical experience considered

Experience & Skills

• 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

Preferred Qualifications

• 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

What Success Looks Like

• Delivers high-quality, scalable applications with integrated GIS and AI capabilities
• Establishes trusted, consistent property and geospatial data capabilities adopted across enterprise platforms
• Increases team velocity through AI tooling and effective mentorship
• Ships a geocoding and matching capability that other teams adopt rather than rebuild