Interested in this AI Product Manager role at USA Clinics Group?
Apply Now →About This Role
Why USA Clinics Group?
Founded by Harvard\-trained physicians with a vision of offering patient\-first care beyond the hospital settings, we’ve grown into the nation’s largest network of outpatient vein, fibroid, vascular, and prostate centers, with 170\+ clinics across the country. Our mission is simple: deliver life\-changing, minimally invasive care, close to home.
We’re building a culture where innovation, compassion, and accountability thrive. While proud of our growth, we’re even more excited about what’s ahead, and the team we’re building to get there. We look forward to meeting you!
Why You'll Love Working with us:
Rapid career advancement Competitive compensation package
Positive, team\-oriented environment Work with cutting\-ed technology
Make a real impact on patients’ lives Join a fast\-growing, mission\-driven company
Position Summary:
The AI Product Manager serves as the bridge between business operations and AI technology by identifying opportunities for AI\-driven innovation, prioritizing initiatives, and overseeing the development and adoption of AI products and solutions across the organization. This role partners with department leaders and technical teams to ensure AI investments deliver measurable business value, operational efficiency, and scalability.
Position Details:
- Location: Northbrook, IL
- Schedule: Full\-time, Monday through Friday on\-site.
- Compensation: $90,000 \- $115,000
Key Responsibilities* Develop and manage the organization's AI product roadmap, prioritizing initiatives that align with strategic business goals.
- Partner with leaders across recruiting, credentialing, revenue cycle, finance, operations, marketing, and clinical support functions to identify high\-impact AI opportunities.
- Gather business requirements, define use cases, and translate operational challenges into AI product solutions.
- Lead cross\-functional AI projects from concept through implementation, adoption, and continuous improvement.
- Establish success metrics, KPIs, and reporting frameworks to measure AI product performance and business impact.
- Coordinate with technical teams, vendors, and stakeholders to ensure timely delivery and successful deployment of AI solutions.
- Develop governance standards, documentation, workflows, and best practices for AI product management.
- Serve as the organization's AI product champion, driving adoption, education, and change management initiatives.
AI \& Automation Responsibilities* Identify, evaluate, and prioritize AI use cases that improve efficiency, reduce costs, increase revenue, or enhance user experience.
- Oversee the development and optimization of AI\-powered applications, copilots, chatbots, agents, workflow automations, and decision\-support tools.
- Utilize AI analytics and user feedback to continuously improve product performance, adoption, and business outcomes.
- Evaluate emerging AI technologies, vendors, and platforms to ensure the organization remains at the forefront of innovation.
Requirements
Minimum Requirements* Bachelor's degree in Business, Technology, Computer Science, Engineering, Healthcare Administration, or related field required.
- Minimum 5 years of product management, business operations, technology, or project management experience.
- Experience managing software, digital products, automation initiatives, or technology implementations.
- Strong analytical, problem\-solving, and stakeholder management skills.
- Demonstrated ability to lead cross\-functional projects and drive organizational change.
Benefits
- Health
- Dental
- Vision
- 401k \& Match
- Paid time off
Salary Context
This $90K-$115K range is in the lower quartile for AI Product Manager roles in our dataset (median: $189K across 161 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 3,823 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At USA Clinics Group, 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 $213,800 based on 583 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000. This role's midpoint ($102K) sits 52% below the category median. Disclosed range: $90K to $115K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
USA Clinics Group AI Hiring
USA Clinics Group has 3 open AI roles right now. They're hiring across AI Product Manager, AI/ML Engineer, LLM Engineer. Based in Northbrook, IL, US. Compensation range: $100K - $115K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. 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 Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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