Technology/AI Lead

Jones Lang LaSalle Americas, Inc.

. Assess facilities, project management, finance, and operations workflows to identify AI, automation, and process redesign opportunities .

Posted 11/9/2026full-timeUnited StatesSenior💰 $132,000 - $150,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in enterprise asset management and predictive maintenance, leveraging AI and automation to optimize workflows and enhance asset data governance. Proficient in SQL and Python for data integration and dashboarding, with a strong focus on process improvement and cross-functional collaboration.

Highest-signal resume keywords

Enterprise Asset ManagementPredictive MaintenanceSQLPythonAI/ML Implementation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Predictive AnalyticsReliability-Centered MaintenanceFMEARoot Cause AnalysisData Quality ControlsProcess MappingWorkflow RedesignETLKPI Dashboard DesignAutomation Solutions

Soft Skills

Cross-Functional CollaborationClient-Facing CommunicationTraining and Adoption Leadership

Tools & Technologies

EAM/CMMS PlatformsPower BIDatabricksIoT-Enabled SystemsCognos

Certifications & Qualifications

PMPCFMCMRPLean Six Sigma

Industry Keywords

Facilities ManagementCapital PlanningAsset LifecycleISO 55001UtilityEnergyPetroleumIndustrialCritical Infrastructure

Tech Stack

Tools & technologies

CognosETLIoTPMPPythonSQL

About the role

Key responsibilities & impact

Assess facilities, project management, finance, and operations workflows to identify AI, automation, and process redesign opportunities
Prioritize opportunities by impact, feasibility, and account objectives
Map current-state processes with on-site teams and design streamlined future-state workflows
Maintain an innovation pipeline for evaluating, piloting, and scaling AI, IoT, and automation capabilities
Build and deploy AI-enabled solutions for predictive maintenance, capital project forecasting, and automated reporting
Architect AI-powered automation within EAM/CMMS platforms, including predictive analytics, automated diagnostics, and intelligent reporting
Design and optimize reliability programs including reliability-centered maintenance, FMEA, root cause analysis, asset criticality analysis, and risk-based PM intervals
Develop asset lifecycle and capital planning models supporting repair-versus-replace and capital deferral decisions
Develop proofs of concept and move prototypes into monitored production solutions
Enhance asset data governance, equipment coding, asset hierarchies, and data quality controls
Build ETL and data links between EAM/CMMS, financial, and project systems using SQL and Python
Design executive KPI dashboards in Power BI or similar tools
Partner with JLL data engineering teams on Databricks to define business logic, metrics, and asset data requirements
Apply responsible AI governance covering data quality, lineage, model monitoring, and evaluation of AI-generated answers
Implement row-level and column-level security, masking, and other access controls
Track and report KPIs 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, develop training materials, run workshops, and provide rollout support
Report to the on-account Sr. Director of Business Operations and collaborate with JLL technology, data, innovation, facilities, operations, and client stakeholders

Requirements

What you’ll need

Bachelor's degree in mechanical engineering, industrial engineering, facilities management, data science, business or a related field
7+ years of experience in enterprise asset management, maintenance and reliability, or facilities operations, including technology implementation
Expert-level experience with one or more EAM/CMMS platforms including configuration, data migration, and multi-site deployment
Demonstrated experience applying AI/ML, predictive analytics, or automation to maintenance and asset management workflows
Strong grounding in predictive and preventive maintenance, reliability-centered maintenance, FMEA, root cause analysis, and asset criticality analysis
Working proficiency in SQL and Python, plus dashboarding tools such as Power BI or Cognos
Experience with asset data governance, data quality, and ETL in an enterprise environment
Demonstrated process improvement experience, such as process mapping, workflow redesign, or Lean/Six Sigma methods
Proven ability to manage cross-functional work in a client-facing environment, lead training and adoption, and explain technical concepts clearly to non-technical stakeholders
This position does not provide visa sponsorship; candidates must be authorized to work in the United States without sponsorship
Preferred: experience in utility, energy, petroleum, industrial, or critical infrastructure environments
Preferred: experience with IoT-enabled building systems or condition monitoring
Preferred: familiarity with ISO 55001 asset management standards and asset lifecycle or capital planning
Preferred: experience with Databricks or integrating EAM data into a lakehouse or semantic layer
Preferred: exposure to LLM-based tools such as RAG, AI agents, or natural-language query
Preferred: background in change management; PMP, CFM, CMRP, Lean Six Sigma, or EAM platform certifications are a plus

Benefits

Comp & perks

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
Supportive culture and comprehensive benefits package prioritizing mental, physical and emotional health