Director of Software Engineering, Research Technology and AI Agents

About JLL And JLL Technologies

JLL is a leading professional services firm that specializes in real estate and investment management. Our vision is to reimagine the world of real estate, creating rewarding opportunities and amazing spaces where people can achieve their ambitions. In doing so, we will build a better tomorrow for our clients, our people, and our communities.

JLL Technologies is a specialized group within JLL. At JLL Technologies, our mission is to bring technological innovation to commercial real estate. We deliver unparalleled digital advisory, implementation, and services solutions to organizations globally. Our goal is to leverage technology to increase the value and liquidity of the world's buildings, while enhancing the productivity and happiness of those that occupy them.

Director Engineering – Research Technology

Location: New York City (On-site)

Role Overview

As Senior Engineering Manager for Research Technology & AI Agents, you will lead the engineering execution of JLL's Research transformation in close partnership with the Product Manager – Research Technology and the Research organization. This is a hands-on leadership role focused on building AI-powered platforms and agents that automate research workflows, democratize insights, and enable advanced analytics at global scale.

You will champion an AI-augmented engineering culture where the team delivers high-quality, reliable, and scalable outcomes at speed by orchestrating AI development tools, enterprise software agents, and strong engineering judgment. A creative and collaborative thinker at heart, you thrive on solving novel problems alongside product managers, researchers, and data scientists — locking arms across disciplines to passionately build what hasn't been built before. Your role is to set the quality bar, establish effective AI-assisted development practices, and ensure the team leverages these tools to maximize velocity without compromising production standards -- all in service of bringing a truly groundbreaking AI-enabled research platform to life.

This role is intentionally co-located in NYC with Product and Research to enable rapid daily iteration between product vision, technical execution, and real researcher feedback — critical for effective AI agent development and deployment.

Key Responsibilities

Engineering Leadership & Execution

• Lead and mentor high-impact engineering team, including senior engineers
• Operate as a hands-on player-coach, contributing to architecture, design, and code reviews
• Establish and evolve team practices for AI-augmented development — ensuring AI coding assistants and enterprise software agents are leveraged effectively across the development lifecycle
• Set clear expectations that engineering judgment, code review rigor, and quality validation remain the responsibility of the engineer, not the AI tool

Partnership with Product & Research

• Partner closely with the Product Management – Research Technology on discovery, roadmap execution, and prioritization
• Work directly with Research users to understand current workflows and future plans and translate them into effective tooling
• Enable rapid iteration cycles through tight collaboration with Product and Research teams

AI Agents & Platform Development

• Design and build AI agents that automate research processes and assist insight generation
• Lead integration of LLMs, agent orchestration, evaluation, and monitoring capabilities
• Build scalable services, APIs, and internal tools that support agent-driven analytics
• Define and enforce quality gates — automated testing, evaluation benchmarks, and guardrails — for agent-driven outputs
• Continuously evaluate and adopt emerging AI development tools and agent platforms available within the enterprise

Architecture & Cloud Platforms

• Design and evolve cloud-native, microservice-based architectures
• Develop and maintain secure, scalable APIs consumed by internal products and platforms
• Collaborate with data, platform, security, and architecture teams to align with enterprise standards, architecture patterns, and Critical Design Reviews (CDRs)
• Participate in and drive high level design reviews for team-owned systems, ensuring alignment with enterprise architecture governance

Delivery & Ways of Working

• Support agile delivery across multiple initiatives and teams
• Manage technical backlogs, dependencies, and delivery risks
• Communicate technical decisions and progress clearly to product and senior stakeholders

Qualifications

Required

• 10+ years of professional software engineering experience, with 3+ years in an engineering leadership role
• Proven experience as a hands-on Engineering Manager (player-coach)
• Strong back-end expertise in Python, Node.js, Java, Go, or C#
• Demonstrated proficiency using AI coding tools and agents to accelerate team delivery, and experience establishing AI-augmented development practices within a team
• Strong ability to set quality standards for reviewing, validating, and debugging AI-generated code across a team
• Experience designing microservice architectures, distributed systems, and complex platforms
• Proven experience building and maintaining RESTful or gRPC APIs
• Deep experience with a major cloud platform (AWS or Azure)
• Solid experience with relational (PostgreSQL, MySQL) and NoSQL (MongoDB, DynamoDB) databases
• Strong understanding of CI/CD, infrastructure-as-code, and containerization (Terraform, Docker, Kubernetes)
• Experience partnering closely with Product Managers and business stakeholders

Preferred

• Experience building AI/ML or LLM-enabled systems, including agent-based workflows
• Experience working with data engineering, analytics, or platform teams
• Front-end experience with React, Angular, or Vue.js for internal tools
• Experience in Commercial Real Estate, Research, Financial Services, or other data-intensive domains
• Experience modernizing legacy platforms and driving technical change

Key skills/competency

• Software Engineering Leadership
• AI Agents & Platform Development
• Cloud-Native Architectures
• Microservices
• RESTful APIs
• Python
• AWS/Azure
• CI/CD
• Agile Methodologies
• Product Management Partnership