Staff Software Engineer

JLL is shaping the future of real estate by combining world-class services, advisory, and technology for its clients. The Staff Software Engineer will design, architect, prototype, and deploy enterprise-grade solutions for complex data and AI problems, while developing AI agents, redesigning data flows, and providing technical leadership across multiple teams.

Responsibilities:

• Lead solution design for complex, cross-functional data and AI problems — from initial discovery through to technical blueprint
• Evaluate and select the right tools and architecture for each problem — no single stack applies across every team you support, so you must be able to reason across different platforms, data sources, and integration patterns
• Define and communicate architecture decisions, trade-offs, and delivery approaches to both technical and non-technical audiences
• Design scalable, modular systems that balance speed with enterprise standards for reliability, security, and maintainability
• Create clear technical documentation: architecture diagrams, data flow maps, API contracts, and solution briefs
• Establish reusable architecture patterns and reference designs that other engineers adopt across engagements
• Use AI coding assistants as your primary development environment for day-to-day solution building — from prototyping through production implementation
• Build and maintain custom plugins/skills for your AI coding assistant that package reusable capabilities for recurring problems across teams
• Redesign and rebuild data pipelines and data flows to unblock use cases — including source integration, transformation logic, and downstream delivery
• Deploy and operate AI agents in production via AWS Bedrock AgentCore
• Translate ambiguous business requirements from stakeholders into concrete technical solutions with minimal hand-holding
• Balance speed of delivery with enterprise standards — your prototypes are production-ready, not throwaway
• Develop intuitive front-end interfaces and dashboards that bring data and AI outputs to life for business users
• Design, build, and deploy AI agents and multi-agent systems that automate complex workflows end-to-end
• Develop and maintain agent skills and plugins — discrete, reusable capabilities that compose into larger agentic pipelines
• Implement and extend Model Context Protocol (MCP) servers and clients to connect agents with enterprise tools, APIs, and data sources
• Design evaluation harnesses, guardrails, and monitoring pipelines to ensure agent reliability and safety in production on AgentCore
• Stay current with the rapidly evolving agentic AI landscape (AI coding assistants, AgentCore, MCP ecosystem) and proactively bring new techniques to the practice
• Define and evolve delivery practices and playbooks used across multiple cross-functional teams
• Serve as the technical escalation point for the most ambiguous or high-stakes problems across the portfolio
• Provide direct input to the hiring manager on recurring patterns and roadmap priorities based on field signal
• Mentor and elevate other engineers on AI-assisted agentic development, plugin design, and rapid delivery
• Embed directly with multiple cross-functional teams simultaneously to co-define problems and co-deliver solutions
• Influence technical direction and build alignment across teams without relying on formal authority
• Communicate complex technical concepts clearly to non-technical business stakeholders — in writing, in meetings, and in presentations
• Foster a collaborative, low-ego culture where speed and quality go hand in hand

Requirements:

• 8–12+ years of software engineering experience, with substantial time in customer-facing or embedded technical delivery roles
• Strong software architecture background — able to independently design and defend system architecture across varied tools and platforms, not tied to one stack
• Direct hands-on experience using AI coding assistants (e.g., Claude, Cursor, GitHub Copilot) as a primary development workflow
• Direct, hands-on experience building and deploying AI agents on AWS Bedrock AgentCore — required
• Experience with Model Context Protocol (MCP) server/client implementation — required
• Data engineering experience — building and redesigning data pipelines and data flows across varied sources
• Full-stack development proficiency — backend services, APIs, and front-end interfaces/dashboards
• Demonstrated experience mentoring engineers and defining technical standards adopted beyond your own work
• Excellent written and verbal communication skills; able to manage multiple concurrent internal stakeholder relationships
• Candidates must be authorized to work in the United States without sponsorship
• experience building custom plugins/skills for these tools is a strong plus