Forward Deploy Engineer

Jones Lang LaSalle Americas, Inc.

Forward Deployed Engineer at JLL, designing solutions for complex data and AI problems. Collaborating closely with product teams to deliver rapid, high-quality prototypes.

Posted 7/24/2026full-timeRemote • California, Illinois • 🇺🇸 United StatesSeniorLead💰 $220,000 - $320,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive experience in architecting end-to-end systems, including building and deploying AI agents with a focus on clear documentation and stakeholder communication. Proficient in developing scalable solutions that balance speed and enterprise standards while fostering collaboration across diverse teams.

Highest-signal resume keywords

15+ Years Software DevelopmentAI Agent DevelopmentModel Context Protocol (MCP)Proficiency in PythonExperience with AWS

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Architecting End-to-End SystemsBuilding AI AgentsDefining Agent SkillsPrototyping SolutionsTechnical Documentation

Soft Skills

Exceptional CommunicationInterpersonal SkillsMentoring Junior EngineersCollaborationNavigating Ambiguity

Tools & Technologies

AWS Agent CoreAI-Augmented Engineering ToolsLangChainReactVue.js

Industry Keywords

Agentic FrameworksCloud PlatformsFast-Paced EnvironmentsEnterprise StandardsTechnical Blueprint

Tech Stack

Tools & technologies

AngularAWSAzureCloudGoogle Cloud PlatformJavaScriptPythonReactVue.js

About the role

Key responsibilities & impact

Lead solution design for complex, cross-functional data and AI problems — from initial discovery through to technical blueprint
Define and communicate architecture decisions, trade-offs, and delivery approaches to both technical and non-technical audiences
Design scalable, modular systems that balance the need for speed with enterprise standards for reliability, security, and maintainability
Participate in architecture reviews, ensuring alignment with enterprise patterns and platform standards
Create clear technical documentation: architecture diagrams, data flow maps, API contracts, and solution briefs
Design and deliver working prototypes for complex data and AI problems within compressed timeframes, often days to weeks
Translate ambiguous business requirements into concrete technical solutions with minimal hand-holding
Balance speed of delivery with enterprise standards — your prototypes are production-ready, not throwaway
Continuously iterate on solutions based on direct feedback from product managers, program leads, and end users
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 — discrete, reusable capabilities that compose into larger agentic pipelines
Implement and extend Model Context Protocol (MCP) servers and clients to connect AI agents with enterprise tools, APIs, and data sources
Design evaluation harnesses, guardrails, and monitoring pipelines to ensure agent reliability and safety in production
Stay current with the rapidly evolving agentic AI landscape and proactively introduce new techniques and tooling to the team
Embed directly with product, program, and engineering teams 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 executive presentations
Mentor and elevate junior engineers, sharing patterns and practices for agentic development, prompt design, and rapid delivery
Foster a collaborative, low-ego team culture where speed and quality go hand in hand.

Requirements

What you’ll need

15+ years Software / Infrastructure Development
Demonstrated ability to architect end-to-end systems — from requirements through deployment — with clear documentation and stakeholder communication
Hands-on experience building AI agents, including defining agent skills, tool use, memory, and multi-step reasoning
Experience with AI-Augmented Engineering (Harness Engineering) — actively use tools like Claude Code, Codex, or equivalent assistants to accelerate coding, documentation, and problem-solving day-to-day.
Direct experience with AWS Agent Core or equivalent — building, deploying, and operating agents in production
Working knowledge of Model Context Protocol (MCP) — including building or consuming MCP servers to connect agents with external systems
Experience with agentic frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or Semantic Kernel
Proficiency in Python and at least one front-end framework (React, Vue.js, or Angular)
Experience with cloud platforms (AWS, Azure, or GCP)
Exceptional communication and interpersonal skills — you can earn trust quickly, navigate ambiguity, and drive alignment across diverse teams
Comfort working in fast-paced environments with shifting priorities and high ownership expectations.

Benefits

Comp & perks

401(k) plan with matching company contributions
Comprehensive Medical, Dental & Vision Care
Paid parental leave at 100% of salary
Paid Time Off and Company Holidays
Early access to earned wages through Daily Pay