Staff Engineer (P4) – Research Technology & AI Agents
Location:
New York City (On-site)
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.
Role Overview
As a Senior Engineer on the Research Technology & AI Agents team, you will be a key technical contributor building AI-powered platforms and agents that automate manual research workflows, democratize insights, and enable advanced analytics at global scale. This is not a traditional software engineering role — you will leverage AI coding assistants, enterprise software agents, and LLM-powered development tools as primary instruments for designing, building, testing, and iterating on production systems at speed.
You will be expected to deliver high-quality, reliable, and scalable outcomes at speed by orchestrating AI tools and human judgment effectively. 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
AI-Augmented Development & Delivery
- Leverage AI coding assistants and enterprise software agents to rapidly develop, test, and iterate on production-quality code
- Own end-to-end delivery of features and systems — from requirements through deployment and monitoring — using AI tools to accelerate every phase of the development lifecycle
- Apply strong engineering judgment to review, validate, and refine AI-generated code for correctness, security, performance, and maintainability
- Design and refine effective prompts, workflows, and agent configurations to maximize the quality and reliability of AI-assisted outputs
- Continuously evaluate and adopt emerging AI development tools and agent platforms available within the enterprise
AI Agents & LLM Integration
- Build and iterate on AI agents that automate research processes and assist with insight generation
- Implement LLM integrations, agent orchestration, evaluation harnesses, and monitoring pipelines
- Experiment rapidly with new AI/ML techniques and translate prototypes into production-grade systems
- Define and enforce quality gates — automated testing, evaluation benchmarks, and guardrails — for agent-driven outputs
Platform & Infrastructure
- Build and maintain cloud-native microservices and scalable APIs consumed by internal products
- Develop internal tools, libraries, and reusable agent patterns that accelerate team velocity
- Implement and improve CI/CD pipelines, infrastructure-as-code, and observability tooling
- Collaborate with data, platform, security, and architecture teams to align with enterprise standards, architecture patterns, and Critical Design Reviews (CDRs)
Collaboration & Communication
- Partner directly with Product and Research users to understand workflows and translate requirements into technical solutions
- Participate actively in agile ceremonies, code reviews, and knowledge-sharing within the team
- Mentor junior engineers on effective AI-augmented development practices, prompt design, and agent usage patterns
- Communicate technical trade-offs and progress clearly to engineering leadership and cross-functional partners
Qualifications
Required
- 8+ years of professional software engineering experience
- Demonstrated proficiency using AI coding tools and agents to develop, test, and ship production software
- Strong ability to review, validate, and debug AI-generated code — you are the quality bar, not the AI tool
- Solid understanding of backend systems, microservice architectures, and distributed systems in Python, Node.js, Java, Go, or C#
- Experience designing and maintaining RESTful or gRPC APIs
- Solid experience with a major cloud platform (AWS, Azure, or GCP)
- Experience with relational databases (PostgreSQL, MySQL) and NoSQL databases (MongoDB, DynamoDB)
- Working knowledge of CI/CD, infrastructure-as-code, and containerization (Terraform, Docker, Kubernetes)
- Strong engineering judgment — knowing when to trust AI output and when to intervene is critical
- Comfort working closely with Product Managers and business stakeholders in a fast iteration cycle
Preferred
- Experience building or deploying LLM-enabled systems, AI agents, or agent orchestration frameworks
- Experience designing evaluation and testing frameworks for AI/agent-generated outputs
- Familiarity with enterprise AI/agent platforms and tool ecosystems
- Experience with data engineering tools and pipelines (e.g., Spark, Airflow, dbt)
- Front-end experience with React, Angular, or Vue.js for internal tools and dashboards
- Experience in Commercial Real Estate, Research, Financial Services, or other data-intensive domains
- Experience modernizing legacy systems or migrating platforms to cloud-native architectures