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About This Role
As a Growth / AI Product Manager, you will work closely with engineering, design, marketing, and sales teams to drive prioritization and delivery of the product roadmap for Neumo’s product organization, with a strong focus on identifying and executing growth opportunities. You’ll focus on market analysis, positioning, customer research, quantitative analysis, and client feedback to inform design and ensure our products meet the needs of Neumo’s clients and prospects. You will translate these insights into effective initiatives and help bring those stories to life — increasingly by building working prototypes yourself alongside partners in engineering and design.
This role is built for a hands-on, full-stack product builder: someone equally comfortable in a discovery interview, a data dashboard, and a code editor. You’ll use AI-assisted development tools like Claude Code to rapidly prototype ideas, build directly within Neumo’s design system to produce high-fidelity, functional prototypes, and treat those prototypes as the primary spec that aligns engineering, design, and stakeholders — reducing ambiguity and accelerating time to ship. You should be comfortable learning new things and taking on new responsibilities, and you won’t hesitate to roll up your sleeves and do the work to turn your concepts into reality.
Duties and Responsibilities
- Own the product lifecycle for the innovation flywheel from market research through product definition, roadmap planning, delivery, and go-to-market strategy.
- Identify customer issues, develop prototypes, drive pilots
- Use AI-assisted coding tools (e.g., Claude Code) to build functional, high-fidelity prototypes directly from Neumo’s design system components, rather than relying solely on static mockups or written specs.
- Treat working prototypes as the primary artifact for aligning engineering, design, and stakeholders — iterating in code to resolve ambiguity before a single engineering ticket is written.
- Rapidly test and validate product concepts with real or synthetic data, wiring up lightweight backends, APIs, or AI model calls as needed to make prototypes feel real.
- Partner with engineering to ensure prototypes translate cleanly into production-quality implementation, understanding enough of the underlying architecture to make credible build-vs-buy and feasibility calls.
- Achieve a clear understanding of the costs of your solution and sustainability alongside price to maintain margin-expanding products.
- Work directly with customers across various markets leveraging user research and real-time feedback to adjust prototypes and enable pilots.
- Work directly with business unit teams and product management and engineering in vertical solutions and platform to enable them to productize the prototype with success, achieving successful transition and timely hand-off.
Education and Experience
- Bachelor’s degree or equivalent work experience.
- 3+ years of experience in product management (B2B software experience preferred).
- 2+ years of experience being technical or technically conversant working with platform technologies and platform teams that are dependent on vertically integrated products.
- Required experience with platform services in a SaaS and SaaS-adjacent model.
- Demonstrated experience using AI-assisted coding tools (e.g., Claude Code, Cursor, GitHub Copilot, or similar) to build functional prototypes or ship production code.
- Experience working within or contributing to a design system (e.g., Figma component libraries, Storybook, shared front-end component code) to build consistent, on-brand prototypes.
- Working knowledge of front-end fundamentals (HTML/CSS/JavaScript or a modern framework such as React) sufficient to read, modify, and extend prototype code.
- Demonstrated experience in building business cases, understanding cost and pricing structures a plus.
- Experience using AI-powered productivity and analysis tools (e.g., Microsoft Copilot, Claude, Rovo, or similar) to support research, documentation, and day-to-day product work is a must.
- Experience with growth methodologies (funnel analysis, experimentation/A-B testing, product-led growth loops) and the analytics tooling to support them (e.g., Amplitude, Mixpanel, or similar).
- Experience in government technology at the state and local level highly preferred.
Knowledge, Skills and Abilities
- Proven track record of shipping software products that deliver business results.
- Demonstrated ability to develop deep customer empathy and articulate customer problems, driven to interact and engage with customers.
- Excellent communication skills (both written and verbal) with the ability to explain complex information in a simple and accurate manner.
- Process, problem-solving, strategic, and continuous improvement mindset.
- Demonstrated success leading cross-functional teams and working collaboratively with stakeholders.
- Ability to influence without direct management authority.
- Ability to thrive in a fast-paced, entrepreneurial environment.
- Comfort moving fluidly between strategy, design, and code — a true full-stack builder mindset.
- Strong judgment about when a prototype is the fastest path to a decision versus when a written spec or conversation will do.
- Experience using tools like JIRA, Figma, and Microsoft 365 Suite, along with AI-assisted development environments (e.g., Claude Code, Cursor, Replit).
- Willingness to travel up to 40%.
Work Environment
The noise level in the work environment is usually moderate as the employee works in an office setting, at an individual workstation, using telephone and computer.
Physical Demands
- Must be able to remain in a stationary position for most of the day.
- Constantly operates a computer and other office productivity machinery, such as a printer/copy machine.
- This position needs to occasionally move about inside the office.
- The person in this position frequently communicates via telephone.
Neumo Summary:
With the backing of four decades of public sector expertise and corporate capability, Neumo has successfully supported government services. Neumo was honored and recognized for four (4) consecutive years as a GovTech 100 Company representing the top 100 companies focused on making a difference in and selling to state and local government agencies across the United States.
Neumo is committed to helping communities thrive and brings a wealth of experience combined with innovation. Today, Neumo offers more administrative and financial support to government officials than any other organization. And with a responsive, client-focused approach, we foster partnerships that give our customers the certainty they need to accomplish more.
Neumo offers a competitive benefits and compensation package and are looking for team members who will thrive in our dynamic environment.
Neumo is an Equal Opportunity Employer. Selection for a position will be made without regard to race, religion, national origin, sex, political affiliation, marital status, non-disqualifying physical handicap, and age.
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 8,943 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At Neumo Holdings LLC, 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 $220,200 based on 862 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200.
Across all AI roles, the market median is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,250; VP: $235,000.
Neumo Holdings LLC AI Hiring
Neumo Holdings LLC has 1 open AI role right now. They're hiring across AI Product Manager. Based in Carrollton, TX, US.
Location Context
Across all AI roles, 6% (521 positions) offer remote work, while 8,351 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,416 roles, $263,811 median); Los Angeles (1,340 roles, $210,000 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 8,943 open positions tracked in our dataset. By seniority: 175 entry-level, 4,132 mid-level, 3,268 senior, and 1,368 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (521 positions). The remaining 8,351 roles require on-site or hybrid attendance.
The market median for AI roles is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 8,943 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,739), AI Product Manager (403), AI Software Engineer (402). 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 (175) are outnumbered by mid-level (4,132) and senior (3,268) 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 1,368 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (521 positions), with 8,351 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 $213,380. Top-quartile roles start at $264,148, and the 90th percentile reaches $319,310. 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 $253,100 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 (1,422 postings), Aws (808 postings), Azure (638 postings), Rag (555 postings), Gcp (457 postings), Pytorch (433 postings), Claude (341 postings), Kubernetes (337 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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