Staff Software Engineer

JLL • Chicago, IL

6d • $187,100 - $229,200 • Onsite

About The Position

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

This is a senior, hands-on technical role. You will identify problems, assess their criticality, drive projects through to successful completion, establish engineering standards, and mentor other engineers. You will use AI coding assistants in your daily workflow and help advance the team from AI-assisted development to AI-enabled products, including agent-based workflows that keep humans in control of consequential decisions.

The role partners with product owners, Legal and AFC stakeholders, technical leads, Information Security, Data Privacy, and other engineering teams. The position is on-site in Chicago, Illinois, and does not provide visa sponsorship; candidates must be authorized to work in the United States without sponsorship.

Requirements

• At least 8 years of professional software engineering experience.
• Strong full-stack development experience, including backend services in Python or Node.js and front-end applications in React; Angular or Vue.js are also considered. Experience should cover product-facing applications and internal tools and dashboards.
• Experience designing, building, and maintaining RESTful APIs and microservice or distributed architectures.
• Hands-on experience with at least one major cloud platform, AWS or Azure, and ability to work across both.
• Working knowledge of CI/CD, infrastructure as code such as Terraform, CloudFormation, or Bicep, and containerization.
• Experience with relational databases such as PostgreSQL, SQL Server, or MySQL, and NoSQL databases such as DynamoDB or Azure Cosmos DB.
• Daily hands-on use of AI coding assistants such as Claude, Cursor, or GitHub Copilot, with the ability to review, validate, and debug AI-generated code.
• Hands-on experience with modern LLM APIs, including prompt engineering, tool use or function calling, structured outputs, and context engineering.
• Ownership of testing strategy across unit, integration, and end-to-end layers, including building or improving test frameworks.
• Experience triaging production failures and independently driving root cause analysis to resolution.
• 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 and ability to partner effectively with non-technical business stakeholders.
• Must be authorized to work in the United States without sponsorship; the position does not provide visa sponsorship.

Nice To Haves

• 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.
• Working knowledge of Databricks, including Spark, Delta Lake, Unity Catalog, or workflows, and experience building data pipelines that feed applications and AI features.
• Experience with Legal, Compliance, or Anti-Financial Crime systems, such as KYC/onboarding, screening, case management, contract lifecycle management, matter management, or e-discovery, or experience in another regulated, data-intensive domain.

Responsibilities

• Lead design and implementation of end-to-end features across React front ends, Python or Node.js services, data stores, and AWS or Azure deployment pipelines; own features from discovery through production support.
• Design solutions for ill-defined or cross-domain problems, taking into account integration with existing Legal and AFC systems, data lineage, and long-term maintainability.
• Define architecture patterns, reference designs, and technical standards adopted by other engineers.
• Build security, confidentiality, and auditability into systems, including role-based access control, data segregation, immutable audit trails, encryption, and retention controls appropriate for legal and regulated data.
• Establish solution structure, CI/CD, infrastructure as code, and DevSecOps practices for new and modernized applications.
• Work with product owners, Legal and AFC stakeholders, and technical leads to design products and enhancements and participate in analysis, coding, and testing.
• Use AI coding assistants and enterprise AI tools to develop, test, and iterate on production-quality code, applying judgment to review and validate AI output.
• Deliver robust implementations that follow best practices and improve related code during development.
• Build and maintain data pipelines and integrations across internal systems, third-party providers, and data platforms, including Databricks where applicable.
• Develop interfaces and dashboards that provide Legal and compliance users with clear, explainable views of data and AI-generated outputs.
• Design, build, and evaluate LLM-enabled features and AI agents for 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 for agent outputs that may affect legal or compliance decisions.
• Build and consume MCP servers and other tool integrations connecting agents to enterprise systems and data sources with least-privilege access.
• Create evaluation harnesses, test sets, and monitoring for AI outputs, including accuracy, drift, source traceability, and logging sufficient for audit and review.
• Partner with Information Security, Data Privacy, and Legal stakeholders to align AI use with JLL policy and applicable regulatory expectations.
• Own testing strategy across unit, integration, and end-to-end layers, and build or improve test frameworks.
• Triage complex production failures, independently drive root cause analysis to resolution, and help others troubleshoot.
• Provide ongoing support, observability, and operational excellence for applications used across the organization.
• Mentor engineers on engineering standards, AI-assisted development practices, and secure design for sensitive data.
• Collaborate with Product Managers, Legal and AFC business partners, and engineering teams in fast iteration cycles, understanding how components support overall product strategy.
• Communicate technical trade-offs clearly to non-technical stakeholders, in writing and in person.

Benefits

• 401(k) plan with matching company contributions
• Comprehensive medical, dental, and vision care
• Paid parental leave at 100% of salary
• Paid time off and company holidays
• Early access to earned wages through Daily Pay
• Supportive culture and comprehensive benefits package prioritizing mental, physical, and emotional health

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed