Staff Software Engineer

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.

Staff Software Engineer – Legal Technology

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.

Role Overview

As a Staff Software Engineer on the Legal Technology team, you will lead the design and implementation of complete features spanning React front ends, Python and Node.js backend services, data layers, and cloud deployment pipelines on AWS or Azure. You will build the systems that support JLL’s Legal and Anti-Financial Crime (AFC) functions, where accuracy, auditability, confidentiality, and data privacy are requirements rather than nice-to-haves.

This is a senior, hands-on technical role. You will discover problems, determine their criticality, and drive your own projects to a successful conclusion, while setting engineering standards and mentoring other engineers. You will use AI coding assistants as part of your daily workflow, and you will help the team move from AI-assisted development to AI-enabled products, including agent-based workflows that keep humans in control of consequential decisions.

Key Responsibilities

Technical Leadership & Architecture

Lead the design and implementation of end-to-end features across the React front end, Python/Node.js services, data stores, and cloud (AWS or Azure) deployment pipeline. Own features from discovery through production support.

Perform solution design for ill-defined or cross-domain problems, accounting for integration with existing Legal and AFC systems, data lineage, and long-term maintainability.

Define architecture patterns, reference designs, and technical standards that other engineers on the team adopt.

Design systems with security, confidentiality, and auditability built in: role-based access control, data segregation, immutable audit trails, encryption, and retention controls appropriate for legal and regulated data.

Set up solution structure, CI/CD, infrastructure as code, and DevSecOps practices for new and modernized applications.

Development & Implementation

Work with product owners, Legal and AFC stakeholders, and technical leads to design new products and enhancements, and participate in analysis, coding, and testing.

Use AI coding assistants and enterprise AI tooling to rapidly develop, test, and iterate on production-quality code, applying sound judgment on when to trust AI output and when to intervene.

Deliver robust implementations that follow best practices with minimal feedback in code review, and improve related code while you are in it.

Build and maintain data pipelines and integrations across internal systems, third-party providers, and data platforms, including Databricks where applicable.

Develop intuitive interfaces and dashboards that give Legal and compliance users clear, explainable views of data and AI-generated outputs.

AI and Agent Enablement

Design, build, and evaluate LLM-enabled features and AI agents that automate or assist Legal and AFC workflows, such as document intake and review, case triage, summarization, and data extraction.

Implement human-in-the-loop controls, guardrails, and approval steps so that agent outputs affecting legal or compliance decisions are reviewed before they are acted on.

Build and consume Model Context Protocol (MCP) servers and other tool integrations that connect agents to enterprise systems and data sources under least-privilege access.

Design evaluation harnesses, test sets, and monitoring for AI outputs, including accuracy, drift, traceability of sources, and logging sufficient to support audit and review.

Partner with Information Security, Data Privacy, and Legal stakeholders so that AI use meets JLL policy and applicable regulatory expectations.

Quality Assurance & Problem Resolution

Own testing strategy across unit, integration, and end-to-end layers, and build or improve test frameworks rather than only writing tests within an existing one.

Triage complicated production failures, drive root cause analysis to resolution independently, and help others troubleshoot.

Provide ongoing support, observability, and operational excellence for applications used across the organization.

Mentorship & Collaboration

Mentor engineers on engineering standards, AI-assisted development practices, and secure design for sensitive data.

Work closely with Product Managers, Legal and AFC business partners, and other engineering teams in fast iteration cycles, understanding how each component fits the overall product strategy.

Communicate technical trade-offs clearly to non-technical stakeholders, in writing and in person.

Qualifications

Required

8+ years of professional software engineering experience.

Strong full stack development experience, with backend services in Python or Node.js and front-end applications in React (Angular or Vue.js also considered), covering both product-facing applications and internal tools and dashboards.

Experience designing, building, and maintaining RESTful APIs and microservice or distributed architectures.

Solid hands-on experience with at least one major cloud platform, AWS or Azure, and the ability to work across both (for example Lambda/Azure Functions, ECS/EKS/AKS, S3/Blob Storage, API Gateway/API Management, IAM/Entra ID, CloudWatch/Azure Monitor).

Working knowledge of CI/CD, infrastructure as code (Terraform, CloudFormation, or Bicep), and containerization.

Experience with relational databases (PostgreSQL, SQL Server, MySQL) and NoSQL databases (for example DynamoDB or Azure Cosmos DB).

Demonstrated fluency in AI-powered software development: daily, hands-on use of AI coding assistants (for example Claude, Cursor, GitHub Copilot), with strong ability to review, validate, and debug AI-generated code.

Hands-on experience with modern LLM APIs, including prompt engineering, tool use/function calling, structured outputs, and context engineering.

Demonstrated ownership of testing strategy across unit, integration, and end-to-end layers, including building or improving test frameworks.

Experience triaging production failures and driving root cause analysis to resolution independently.

Experience building software that handles confidential or regulated data, with working knowledge of secure development practices, access control, and audit logging.

Excellent written and verbal communication skills, with the ability to partner effectively with non-technical business stakeholders.

Preferred

Experience building or deploying AI agents or agent orchestration frameworks, including multi-step workflows with tool use.

Experience building MCP servers or clients, or working with enterprise agent platforms such as AWS Bedrock AgentCore or Azure AI Foundry.

Experience designing evaluation and testing frameworks for AI- or agent-generated outputs.

Working knowledge of Databricks (Spark, Delta Lake, Unity Catalog, or workflows) and building data