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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.
Principal Product Manager, Enterprise AI Product and Strategy
Role Overview
Real estate is the largest asset class on earth: $393 trillion, worth more than global equities and debt combined, and still one of the least automated industries anywhere. JLL sits at the heart of it, a Fortune 200 company advising on the buildings the world works in and the capital that moves them.
Every employee at JLL now has AI in their hands, at different levels of capability and cost. Deciding which products the company offers, to whom, and under what guardrails is an ongoing product challenge, and this role will own that. We are looking for someone who can see past what AI can do today to where the frontier is heading and use that foresight to guide JLL's strategy.
Key Responsibilities
You'll own JLL’s “Enterprise AI” product strategy: which products we buy, which products we build, and how we deploy both to create value at scale. That means running vendor evaluation and selection, keeping the portfolio current as the market shifts, and making build-versus-buy calls as new options emerge. It also means actively tracking the trajectory of frontier AI capabilities (model releases, agentic systems, cost curves) and translating that into a view of what JLL's products and workforce will need 12–24 months out. A critical input into that strategy is how it interacts with business- and function-driven AI initiatives elsewhere in the organization. Understanding those dependencies and shaping the roadmap around them is one of your key responsibilities.
You'll spend significant time with users and business lines doing discovery: learning what they're trying to get done, where today's products fall short, and which workarounds people have built on their own that point to a product gap. That discovery is yours to own and feeds everything else in this role: the portfolio strategy, the build-versus-buy calls, and the governance model.
You'll partner with governance and risk teams to make sure the products you bring into the portfolio, and how they're rolled out, meet JLL's responsible AI standards.
You'll build, but selectively: you're looking for the specific, high-value cases where something purpose-built for our industry is the right call: capabilities distinctive enough to justify JLL's own investment, rather than general ones the market will commoditize. Where that bar is met, you'll scope it, advocate for it, and see it through.
You'll define and track adoption and value metrics for the Enterprise AI portfolio (usage, fluency progression, and business outcomes) and report progress against Accelerate 2030 commitments. You'll be measured on those numbers, on how defensible your product and vendor recommendations are when tested by finance and business leadership, and on whether the strategy stays coherent with what the rest of the business is doing in AI.
You’ll work closely with the Enterprise AI enablement team to achieve our overall goals and metrics. Adoption is a means, not the goal. Ultimately, you're accountable for value delivered- benefits realized net of cost. You will constantly strive to increase the intelligence delivered per dollar of spend.
Required Experience
- 8+ years of product management or product leadership experience, including scaling products and driving adoption in a complex, matrixed enterprise.
- Direct experience evaluating or selecting AI vendors or models, including the tradeoffs between a bought product and a built one.
- Experience with enterprise AI assistants or employee-facing AI tools, preferably in real estate or another large matrixed enterprise.
- Deep fluency with frontier AI and agent concepts, including where model capabilities and costs are likely to be in 12–24 months. You can evaluate a vendor's technical claims yourself and make roadmap bets ahead of the market.
- Strong judgment on sequencing and prioritizing a multi-product roadmap where products sit at different lifecycle stages, from active growth to maintenance.
- Familiarity with responsible AI practices and governance frameworks for scaling AI safely across a large organization.
- A track record of developing and defending product or portfolio strategy at the executive level, grounded in rigorous analysis.
- Strong financial analysis and cost-modeling skills, including building and defending a total-cost-of-ownership or unit-economics model yourself.
- Experience building user-centric products that balance intuitiveness with utility.
- Experience working in global, matrixed organizations across geographies and business lines, including a track record of driving a cross-functional decision to closure in a large, distributed organization.
- Exceptional communication and influence: you can break down complex problems, make a clear case for your perspective, and persuade others with logic and data.
Preferred Experience
- MBA or advanced degree in business, technology, or a related field preferred.
- Background in strategy consulting or FP&A, with hands-on financial modeling as part of the job.
- Active engagement with frontier AI research, model releases, and practitioner communities, with a demonstrated point of view on where AI capabilities are headed and what that means for the enterprise.
This position does not provide visa sponsorship. Candidates must be authorized to work in the United States without sponsorship.
Expected compensation for this position:
215,300.00 – 263,700.00 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 –Chicago, IL
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
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.
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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 [email protected]. 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.
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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.
Salary Context
This $215K-$263K range is above the 75th percentile for AI Product Manager roles in our dataset (median: $194K across 123 roles with salary data).
View full AI Product Manager salary data →Role Details
About This Role
AI Product Managers define what AI features get built and why. They translate business problems into ML-solvable tasks, work with engineering to scope model requirements, and own the metrics that determine if an AI feature is working. The role requires a rare combination of technical fluency and product instinct.
Unlike traditional product management, AI PM work involves managing uncertainty at a fundamental level. Your model might work 90% of the time. What happens the other 10%? What's the user experience when the AI is wrong? How do you measure 'good enough' for a probabilistic system? These questions don't have easy answers, and the AI PM is the person responsible for finding them.
Across the 9,079 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At JLL, this role fits into their broader AI and engineering organization.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
What the Work Looks Like
A typical week includes: reviewing model evaluation results with the ML team, defining success metrics for a new AI feature, conducting user research on how customers respond to AI-generated outputs, writing product requirements that include accuracy thresholds and fallback behaviors, and presenting the AI roadmap to leadership. You're the translator between technical capability and business value.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
Skills in Demand for This Role
Technical fluency with ML concepts is essential, though you won't be writing models. Expect to understand training data, evaluation metrics, model limitations, and responsible AI practices. SQL and basic Python are increasingly expected. Experience with A/B testing, data analysis, and product analytics is baseline. Understanding LLM capabilities and limitations is now a core requirement.
The differentiator is AI-specific product thinking: knowing when to use ML vs. heuristics, understanding the cost of training data collection, designing graceful degradation for model failures, and building products that improve with usage data. Experience with AI safety, bias mitigation, and responsible AI deployment is increasingly important.
Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
Compensation Benchmarks
AI Product Manager roles pay a median of $220,200 based on 947 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $229,300. This role's midpoint ($239K) sits 9% above the category median. Disclosed range: $215K to $263K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
JLL AI Hiring
JLL has 3 open AI roles right now. They're hiring across AI Product Manager, AI/ML Engineer. Positions span Chicago, IL, US, Chicago, IL. Compensation range: $250K - $263K.
Location Context
AI roles in Chicago pay a median of $193,440 across 429 tracked positions. That's 9% below the national median.
Career Path
Common paths into AI Product Manager roles include Product Manager, Data Analyst, Technical Program Manager.
From here, career progression typically leads toward Director of AI Product, VP Product, Head of AI.
The most effective path is PM experience plus self-directed AI education. Take Andrew Ng's courses, build a small ML project, and learn enough Python to read model evaluation code. The goal isn't to become an ML engineer. It's to have credibility in technical conversations and to understand what's possible, what's hard, and what's a bad idea.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
AI Hiring Overview
The AI job market has 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 roles).
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
The AI Job Market Today
The AI job market spans 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (106) are outnumbered by mid-level (4,384) and senior (3,343) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $256,000 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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