Senior Forward-Deployed AI Engineer

JLL; Chicago (IL); On-site; USD 150,000 - 280,000; Full time

Benefits offered by this job

401(k) with match

Medical, Dental & Vision

Paid parental leave

Paid time off

Daily Pay

Job summary

JLL in Chicago is seeking a Staff Forward Deployed Engineer to rapidly design, prototype, and deploy AI-driven solutions across cross-functional teams, delivering working prototypes in days with enterprise-grade quality.

You will own architecture across multiple engagements, build AI agent-based pipelines on AWS Bedrock AgentCore, mentor other engineers, and define reusable patterns that raise delivery velocity while maintaining security and reliability.

Qualifications

• 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; experience building custom plugins/skills for these tools is a strong plus
• 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

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

Skills

AI agents

Data architecture

Full-stack development

Software architecture

AI coding assistants

Bedrock/AgentCore

MCP protocol

Stakeholder management

Mentoring engineers

Team collaboration

Tools

Claude

Cursor

GitHub Copilot

AWS Bedrock

Job description

JLL in Chicago is seeking a Staff Forward Deployed Engineer to rapidly design, prototype, and deploy AI-driven solutions across cross-functional teams, delivering working prototypes in days with enterprise-grade quality.

You will own architecture across multiple engagements, build AI agent-based pipelines on AWS Bedrock AgentCore, mentor other engineers, and define reusable patterns that raise delivery velocity while maintaining security and reliability.