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Jones Lang LaSalle

Advises on and manages commercial real estate

Technology/AI Lead

Mechanical Maintenance and Reliability EngineeringPosted on Nov 9
Full-time

About the Job

Requirements

  • A bachelor's degree in mechanical engineering, industrial engineering, facilities management, data science, business, or a related field is required.
  • At least 7 years of experience in enterprise asset management, maintenance and reliability, or facilities operations, including technology implementation, is required.
  • Expert-level experience with one or more enterprise asset management or computerized maintenance management system platforms, including configuration, data migration, and multi-site deployment, is required.
  • Demonstrated experience applying artificial intelligence or machine learning, predictive analytics, or automation to maintenance and asset management workflows is required.
  • Knowledge of predictive and preventive maintenance, reliability-centered maintenance, failure mode and effects analysis, root cause analysis, and asset criticality analysis is required.
  • Working proficiency in SQL and Python and experience with dashboarding tools such as Power BI or Cognos are required.
  • Experience with asset data governance, data quality, and extract, transform, and load processes in an enterprise environment is required.
  • Demonstrated process improvement experience, such as process mapping, workflow redesign, or Lean/Six Sigma methods, is required.
  • Ability to manage cross-functional work in a client-facing environment, lead training and adoption, and explain technical concepts clearly to non-technical stakeholders is required.
  • Candidates must be authorized to work in the United States without visa sponsorship.

Responsibilities

  • Assess facilities, project management, finance, and operations workflows across the account to identify opportunities for artificial intelligence, automation, and process redesign, and prioritize them by impact, feasibility, and alignment with account objectives.
  • Map current-state processes with on-site teams, identify bottlenecks and manual effort, and design streamlined future-state workflows before applying technology.
  • Maintain an innovation pipeline for evaluating, piloting, and scaling emerging artificial intelligence, Internet of Things, and automation capabilities relevant to utility and critical infrastructure facilities.
  • Build and deploy artificial intelligence-enabled solutions for predictive maintenance of critical building systems, artificial intelligence-assisted capital project forecasting, and automated reporting.
  • Architect artificial intelligence-powered automation within the account's enterprise asset management and computerized maintenance management system platforms, including predictive analytics, automated diagnostics, and intelligent reporting to reduce manual effort for facilities teams.
  • Design and optimize reliability programs, including reliability-centered maintenance, failure mode and effects analysis, root cause analysis, asset criticality analysis, and risk-based preventive maintenance intervals.
  • Develop asset lifecycle and capital planning models that use maintenance and condition data to inform repair-versus-replace and capital deferral decisions.
  • Develop proofs of concept to validate proposals, then move prototypes into production-grade, monitored solutions.
  • Enhance asset data governance standards, including equipment coding, asset hierarchies, and data quality controls, so the asset register is accurate and ready for artificial intelligence applications.
  • Build extract, transform, and load processes and data links between enterprise asset management and computerized maintenance management systems, financial systems, and project systems using SQL and Python, including structure for unstructured data such as work orders and inspection reports.
  • Design executive key performance indicator dashboards in Power BI or similar tools covering preventive maintenance compliance, mean time between failures, mean time to repair, downtime trends, backlog, and cost performance.
  • Partner with JLL's data engineering teams on the Databricks platform, defining business logic, metric definitions, and asset data requirements that feed the governed semantic layer and natural-language query tools.
  • Apply governance frameworks for responsible artificial intelligence use in the regulated utility environment, covering data quality, lineage, model performance monitoring, and evaluation of artificial intelligence-generated answers against trusted data.
  • Implement access controls such as row- and column-level security and masking so solutions respect data classification, privacy, cybersecurity, and client technology standards.
  • Track and report initiative performance against agreed key performance indicators, including cost savings, downtime reduction, forecast accuracy, and user adoption.
  • Present business cases, progress updates, and innovation roadmaps to JLL account leadership and client stakeholders.
  • Train facilities and project teams on new artificial intelligence-enabled tools, translate technical capabilities into practical workflows, develop training materials, run workshops, and provide user support during rollout.

Desired Qualifications

  • Experience in utility, energy, petroleum, industrial, or critical infrastructure environments is preferred.
  • Experience with Internet of Things-enabled building systems or condition monitoring is preferred; energy optimization experience is a plus given the Gen 2 roadmap.
  • Familiarity with ISO 55001 asset management standards and asset lifecycle or capital planning is preferred.
  • Experience with Databricks or integrating enterprise asset management data into a lakehouse or semantic layer is preferred.
  • Exposure to large language model-based tools such as retrieval-augmented generation, artificial intelligence agents, or natural-language query applied to maintenance or asset data is preferred.
  • A background in change management is preferred; Project Management Professional, Certified Facility Manager, Certified Maintenance and Reliability Professional, Lean Six Sigma, or enterprise asset management platform certifications are a plus.

About the Company

Jones Lang LaSalle

Advises on and manages commercial real estate

Jones Lang LaSalle, known as JLL, advises property owners, occupiers and investors on commercial real estate worldwide. Its teams broker leases and property sales, arrange financing, value assets, manage buildings and workplaces, and oversee construction projects for businesses, institutions and governments. LaSalle Investment Management invests client capital in private property and real estate securities, while JLL Technologies develops workplace software and data tools. The company earns commissions, service fees, investment management fees and software revenue, with some client operating costs reimbursed through contracts. JLL took its current form through a 1999 merger and is headquartered in Chicago, Illinois.

Company size
10,001+
Company stage
IPO
Headquarters
Chicago, IL
Founded
1999

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