Director, Software Engineering
Role details
Job location
Tech stack
Job description
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. 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 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 a 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.
Requirements
- 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.