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Join Our Team at Realityworks AI!
Who We Are
RW Thrive is a growth\-focused, 100% employee\-owned holding company building a network of education\-focused businesses, including Realityworks, CreXo, and Realityworks AI. Together, these companies develop experiential learning technology, AI\-enabled healthcare simulation, and training solutions used by educators and workforce development programs worldwide. This role is employed by Realityworks AI, a subsidiary of RW Thrive.
The Opportunity
Are you passionate about building technology that makes a meaningful impact? As the Head of Software Development, you will lead the technical vision, strategy, and delivery of an innovative software portfolio spanning Realityworks, CreXo, and Realityworks AI. In this highly visible leadership role, you'll help shape the future of AI\-powered learning and workforce solutions by bringing together cloud applications, embedded systems, physical products, and simulation technologies.
As the organization's senior software engineering leader, you'll drive software architecture, AI strategy, engineering excellence, and product delivery while leading the Quality \& Validation, Simulation Systems, and Embedded Design teams and guiding a network of engineering partners. Success in this role requires balancing innovation with execution—determining what should be built, when it should be built, and how it should be built to create meaningful customer impact.
Bring your vision, leadership, and technical expertise to help shape the future of learning, workforce development, and AI\-driven solutions.
Why Join Us?
When you join Realityworks AI, you become a co\-owner in a company that values your contributions and rewards your success. Our employee\-centered culture is built on collaboration, innovation, and shared achievement.
We offer a robust benefits package, including:
- Employee Stock Ownership Plan (ESOP): 100% company\-funded and designed to grow in value as we succeed together
- Health, Dental, and Life Insurance: Comprehensive coverage to support your well\-being
- 401(k) Retirement Plan: With company match up to 6%
- Generous Paid Time Off: Over 20 days annually, plus 10 paid holidays
- Wellness Incentives: Gym reimbursement and healthy living rewards
- Family\-Friendly Benefits: Paid maternity, paternity, and adoption leave
- Flexible Spending Accounts: Including dependent care coverage
- Disability Coverage: Long\-term and short\-term
- Education Support: Tuition assistance for continued learning
- Community Engagement: Paid volunteer time and donation matching
Compensation
- The expected base compensation range for this position is $159,000 – $238,000 annually, determined by experience, qualifications, and geographic location. This position is eligible to participate in the company’s annual bonus program.
Key Responsibilities
- Owns the technical architecture, platform roadmap, and engineering standards across cloud applications, embedded systems, physical products, and simulation technologies
- Defines and executes the organization's AI software strategy, including LLMs, SLMs, speech technologies, computer vision, and intelligent agents
- Leads software delivery and release execution across all product lines, ensuring alignment with business priorities and product roadmaps
- Builds and protects the company's differentiated technical IP, including patient\-state modeling, grading engines, clinical scenario modeling, and AI training\-data pipelines
- Directs and optimizes an elastic network of outsourced engineering partners across product management, software engineering, AI/ML, QA, and DevOps functions
- Provides leadership and oversight to the Quality \& Validation, Simulation Systems, and Embedded Design teams
- Establishes scalable engineering processes, development standards, platform strategies, and technology roadmaps that support long\-term growth
- Partners with product, clinical, hardware, AI, and customer\-facing teams to evaluate opportunities, prioritize investments, and deliver innovative customer solutions
- Performs other duties as assigned
What You’ll Bring
- Bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, Electrical Engineering, or a related technical discipline; an equivalent combination of education and progressively responsible software engineering experience will also be considered
- 8\+ years of software engineering experience
- Demonstrated experience directing outsourced/offshored engineering teams at scale
- Experience with SaaS platforms and cloud architectures
- Strong understanding of modern AI/LLM technologies
Desired Qualifications
- Medical simulation, healthcare technology, EdTech, or training systems experience
- Experience with conversational AI, speech technologies, or local AI deployments
- Familiarity with hardware/software integration environments
- Experience scaling products from prototype to commercial deployment
Work Location
- This is a remote position with regular travel to our Eau Claire, WI headquarters, expected approximately twice per month for team collaboration, planning, and business meetings. Given this travel cadence, we're prioritizing candidates based in the Minneapolis\-St. Paul area.
Travel Requirements
- Occasional (\<10%) domestic and international travel for customer meetings, vendor and partner engagements, and tradeshows
Learn More
- Explore our mission and the impact we’re making in education at www.realityworks.com and crexo.com.
*Realityworks AI is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.*
Salary Context
This $159K-$238K range is above the median 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 Realityworks, 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 $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 ($198K) sits 9% below the category median. Disclosed range: $159K to $238K.
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.
Realityworks AI Hiring
Realityworks has 1 open AI role right now. They're hiring across AI Product Manager. Based in Eau Claire, WI, US. Compensation range: $238K - $238K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 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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