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JLL empowers you to shape a brighter way.

Our people at JLL are shaping the future of real estate for a better world by combining world class services, advisory and technology for our clients. We are committed to hiring the best, most talented people and empowering them to thrive, grow meaningful careers and to find a place where they belong. Whether you've got deep experience in commercial real estate, skilled trades or technology, or you're looking to apply your relevant experience to a new industry, join our team as we help shape a brighter way forward.

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

This position does not provide visa sponsorship. Candidates must be authorized to work in the United States without sponsorship.

Estimated compensation for this position:

240,000.00 - 325,000.00 USD per year

This range is an estimate and actual compensation may differ. Final compensation packages are determined by various considerations including but not limited to candidate qualifications, location, market conditions, and internal considerations.

Location:

On-site -New York, NY

If this job description resonates with you, we encourage you to apply, even if you don't meet all the requirements. We're interested in getting to know you and what you bring to the table!

Personalized benefits that support personal well-being and growth:

JLL recognizes the impact that the workplace can have on your wellness, so we offer a supportive culture and comprehensive benefits package that prioritizes mental, physical and emotional health. Some of these benefits may include:

• 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

At JLL, we harness the power of artificial intelligence (AI) to efficiently accelerate meaningful connections between candidates and opportunities. Using AI capabilities, we analyze your application for relevant skills, experiences, and qualifications to generate valuable insights about how your unique profile aligns with the specific requirements of the role you're pursuing.

JLL Privacy Notice

Jones Lang LaSalle (JLL), together with its subsidiaries and affiliates, is a leading global provider of real estate and investment management services. We take our responsibility to protect the personal information provided to us seriously. Generally the personal information we collect from you are for the purposes of processing in connection with JLL's recruitment process. We endeavour to keep your personal information secure with appropriate level of security and keep for as long as we need it for legitimate business or legal reasons. We will then delete it safely and securely.

For more information about how JLL processes your personal data, please view our Candidate Privacy Statement.

For additional details please see our career site pages for each country.

For candidates in the United States, please see a full copy of our Equal Employment Opportunity policy here.

Jones Lang LaSalle ("JLL") is an Equal Opportunity Employer and is committed to working with and providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation because of a disability for any part of the employment process - including the online application and/or overall selection process - you may email us at HRSCLeaves@jll.com. This email is only to request an accommodation. Please direct any other general recruiting inquiries to our Contact Us page > I want to work for JLL.

Pursuant to the Arizona Civil Rights Act, criminal convictions are not an absolute bar to employment.

Pursuant to Illinois Law, applicants are not obligated to disclose sealed or expunged records of conviction or arrest.

Pursuant to Columbia, SC ordinance, this position is subject to a background check for any convictions directly related to its duties and responsibilities. Only job-related convictions will be considered and will not automatically disqualify the candidate.

California Residents only

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Pursuant to the Los Angeles Fair Chance Initiative for Hiring Ordinance, JLL will consider for employment all qualified Applicants, including those with Criminal Histories, in a manner consistent with the requirements of applicable state and local laws, including the City of Los Angeles' Fair Chance Initiative for Hiring Ordinance.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Accepting applications on an ongoing basis until candidate identified.