Technology/AI Lead

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Role Summary

The Technology/AI Lead will design, build, and deploy AI-enabled solutions and process improvements across the account. The work spans facilities management, project management, finance, and operations. This is a hands-on, blended role. It pairs deep EAM/CMMS and reliability engineering expertise with AI-powered automation and analytics, along with the operational judgment to find where intelligent automation will cut cost, reduce downtime, and improve service delivery across a complex, geographically distributed utility portfolio. The Technology/AI Lead will turn account pain points into working solutions, take them from proof of concept to production, and measure their impact against KPIs agreed with client leadership. This hybrid role combines in-office collaboration with flexibility to work remotely, plus some travel to client sites as needed.

Responsibilities

Opportunity identification and process improvement

• Assess facilities, project management, finance, and operations workflows across the account to find opportunities for AI, automation, and process redesign. Prioritize them by impact, feasibility, and fit 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 a structured innovation pipeline for evaluating, piloting, and scaling emerging AI, IoT, and automation capabilities relevant to utility and critical infrastructure facilities.

AI solution design and delivery

• Build and deploy AI-enabled solutions for predictive maintenance of critical building systems, AI-assisted capital project forecasting, and automated reporting.
• Architect AI-powered automation within the account's EAM/CMMS platforms, including predictive analytics, automated diagnostics, and intelligent reporting that reduce manual effort for facilities teams.
• 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 that use maintenance and condition data to inform repair-versus-replace and capital deferral decisions.
• Develop POCs to validate proposals, then move prototypes into production-grade, monitored solutions.

Asset data and analytics

• Enhance asset data governance standards, including equipment coding, asset hierarchies, and data quality controls, so the asset register is accurate and AI-ready.
• Build ETL and data links between EAM/CMMS, financial, and project systems using SQL and Python, including structure for unstructured data such as work orders and inspection reports.
• Design executive KPI dashboards in Power BI or similar tools covering PM compliance, MTBF/MTTR, downtime trends, backlog, and cost performance.
• Partner with JLL's data engineering teams on the Databricks platform, defining the business logic, metric definitions, and asset data requirements that feed the governed semantic layer and natural-language query tools.

Governance, security, and compliance

• Apply governance frameworks for responsible AI use in the regulated utility environment, covering data quality, lineage, model performance monitoring, and evaluation of AI-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.

ROI measurement and reporting

• Track and report initiative performance against agreed 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.

Adoption and enablement

• Train facilities and project teams on new AI-enabled tools, translate technical capability into practical workflows, develop training materials, run workshops, and provide user support during rollout.

Required Qualifications

• 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 reliability methods: 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.

Preferred Qualifications

• Experience in utility, energy, petroleum, industrial, or critical infrastructure environments.
• Experience with IoT-enabled building systems or condition monitoring. Energy optimization experience is a plus given the Gen 2 roadmap.
• Familiarity with ISO 55001 asset management standards and asset lifecycle or capital planning.
• Experience with Databricks, or with integrating EAM data into a lakehouse or semantic layer.
• Exposure to LLM-based tools such as RAG, AI agents, or natural-language query, applied to maintenance or asset data.
• Background in change management. PMP, CFM, CMRP, Lean Six Sigma, or EAM platform certifications are a plus.

Reporting and Collaboration

The Technology/AI Lead will report to the on-account Sr. Director of Business Operations. They will collaborate closely with JLL's technology, data, and innovation teams and with client's facilities, operations, and other stakeholders. This position does not provide visa sponsorship. Candidates must be authorized to work in the United States without sponsorship. Expected compensation for this position: 132,000.00 – 150,000.00 USD per year Final compensation packages are determined by various considerations including but not limited to candidate qualifications, location, market conditions, and internal considerations. Location: On-site –Albany, NY, Northborough, MA Job Tags: Real Estate Industry Knowledge 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 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

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