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About This Role
At HUB International, we are a team of entrepreneurs. We believe in protecting and supporting the aspirations of individuals, families, and businesses. We help our clients evaluate their risks and develop solutions tailored to their needs. We believe in empowering our employees to learn, grow, and make a difference. Our structure enables our teams to maintain their own unique, regional culture while leveraging support and resources from our corporate centers of excellence.
HUB is a global insurance and employee benefits broker, providing a boundaryless array of business insurance, employee benefits, risk services, personal insurance, retirement, and private wealth management products and services. With over $5 billion in revenue and almost 20,000 employees in 600 offices throughout North America, HUB has grown substantially, in part due to our industry leading success in mergers and acquisitions.
Role Summary
This role supports product management for the marketing organization's AI program: helping define what we build across teams, how new tools and applications get adopted across disciplines, and how we measure impact. This role also maintains a system\-level view of the marketing technology stack, tracking platform usage and overlap and surfacing recommendations for the VP's review, while individual tool owners retain their contracts and vendor relationships.
This formalizes a function within Marketing Operations that has been a key focus from the start, moving AI work from proofs of concept and fragmented experimentation toward scaled, owned infrastructure including product development and executional rigor. We've already built a growing number projects and skills with impressive adoption across the team. What started as a shared priority now needs a dedicated owner to measure what's working, embed it into everyday workflows, and support the Marketing department in shaping what AI looks like at HUB from a marketing lens.
Key Responsibilities
AI Program Product Management
- Support the roadmap for Marketing AI initiatives built and scaled across marketing disciplines, moving from pilot projects to systemic, owned infrastructure
- Manage the Marketing AI intake, triage and publishing pipeline, including testing, review and enterprise publishing steps
- Lead the Marketing AI Task Force, including use case tracking, training and cross\-functional coordination
- Track impact measurement across teams, including time savings, adoption and return on investment
- Serve as the marketing point of contact for enterprise AI initiatives, partnering with enterprise stakeholders on publishing, naming and access governance
- Help identify transformational, multi\-step AI initiatives, in partnership with the VP
MarTech Stack Stewardship
- Maintain a current view of the full marketing technology stack, including what each platform does and where capabilities overlap
- Track platform performance against team needs and surface recommendations on what to add, consolidate or retire for the VP's review
- Flag duplicative tools before renewal or purchase decisions
- Support tool owners with a system\-level perspective while leaving contract ownership and vendor relationships with the requesting team
AI Governance \& Enterprise Support
- Support the VP, Marketing Operations, in maintaining the AI governance policy and approval process
- Build and maintain the AI playbook, training materials and FAQ resources as the program matures
- Support enterprise AI initiatives that touch marketing, translating enterprise direction into team\-level application.
What This Person Steps Into
- A Marketing AI Task Force foundation that has evolved into a group of builders and an active AI community across the marketing team — a track record that made this initiative the blueprint for HUB's enterprise Claude rollout to 20,000\+ employees
- Several published Claude Projects supporting team efficiency, with an active enterprise publishing pipeline and an AI impact framework and AI Source of Truth to track adoption and outcomes
- A defined AI intake, triage, and governance process, including a documented time\-tracking and deliverables framework that ties workstream activity to IT dependencies (including the Enterprise AI \& Automation and Enterprise Security teams) and build status
- A MarTech assessment of knowledge and project management tools marketing technology assessment underway across Seismic, MS SharePoint, Confluence, Jira, and Adobe Workfront, with a prioritized recommendation targeted for Q3
- A growing marketing technology stack across SEO/GEO, Design, Digital Experience/Content Management, Marketing Automation, content, campaign, reporting/analytics, and workflow automation tools that does not yet have a dedicated owner
Qualifications
- 5\+ years of experience supporting or owning a technology platform, product, or systems roadmap, ideally within marketing or a related function
- Product Management or Project Management experience, experience with agile, kanban frameworks, etc
- A track record of building intake, workflow, or measurement infrastructure that teams adopt
- Experience building new programs or processes from the ground up, not just optimizing existing ones
- Comfort evaluating and speaking to non\-technical stakeholders about technical tradeoffs and platform decisions
- Exposure to measuring adoption, productivity, or return on investment for a tool or program
- AI\-specific experience and relevant certifications (e.g., prompt engineering, AI governance, or platform\-specific credentials) are a plus, not a requirement. The right person will bring the same rigor to AI that a strong product owner brings to any platform.
JOIN OUR TEAM
Do you believe in the power of innovation, collaboration, and transformation? Do you thrive in a supportive and client focused work environment? Are you looking for an opportunity to help build and drive change in a rapidly growing and evolving organization? When you join HUB International, you will be part of a community of learners and doers focused on our Core Values: entrepreneurship, teamwork, integrity, accountability, and service.
*The expected salary range for this position is $110,000 to $130,000 and will be impacted by factors such as the successful candidate’s skills, experience and working location, as well as the specific position’s business line, scope and level. HUB International is proud to offer comprehensive benefit and total compensation packages which could include health/dental/vision/life/disability insurance, FSA, HAS and 401(k) accounts, paid\-time\-off benefits such as vacation, sick, personal, floating holidays and company holidays. In addition, eligible annual bonuses, equity and commissions may be available for some positions.*
Department Marketing
Required Experience: 5\-7 years of relevant experience
Required Travel: No Travel Required
Required Education: Bachelor's degree (4\-year degree)
HUB International Limited is an equal opportunity employer that does not discriminate on the basis of race/ethnicity, national origin, religion, age, color, sex, sexual orientation, gender identity, disability or veteran's status, or any other characteristic protected by local, state or federal laws, rules or regulations.
E\-Verify Program
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Salary Context
This $110K-$130K range is in the lower quartile for AI Product Manager roles in our dataset (median: $185K across 167 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 4,317 AI roles we're tracking, AI Product Manager positions make up 4% of the market. At HUB International, 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 Required
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 $217,100 based on 471 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($120K) sits 45% below the category median. Disclosed range: $110K to $130K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
HUB International AI Hiring
HUB International has 1 open AI role right now. They're hiring across AI Product Manager. Based in Chicago, IL, US. Compensation range: $130K - $130K.
Location Context
AI roles in Chicago pay a median of $192,900 across 197 tracked positions. That's 10% 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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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