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About This Role
CodePath is the largest educator of college computer science students in the country. We have trained over 40,000 students from 1,000\+ universities. Our partners include Amazon, Google, Meta, and 4,000\+ companies across the industry. We’ve been training the next generation of technical talent for nearly a decade, and we just launched a $150M initiative with Anthropic, building one of the most ambitious AI workforce programs in the world.
We're now expanding into new markets and scaling our team so we can move at the speed AI is transforming the workforce. People joining CodePath now will have the opportunity to help architect the next frontier of our work.
We are building toward millions of learners, hundreds of millions in revenue, and billions in economic impact for a generation of technical talent who have historically been locked out of tech. If you want to own something and be part of a 0\-to\-1 journey at an organization moving at the speed of AI, we think you’d love it here.
About the Role
Location: Remote
Role Type: Full\-Time
Reporting to: Chief Product Officer
Compensation: $200,000 to $232,000 per year
- Base salary: $135,000 \- $175,000
- Total compensation includes the base salary plus a guaranteed monthly supplement
The AI Corps opportunity
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AI Corps is a fellowship program that sources, trains, and deploys applied AI specialists into organizations. Fellows complete an intensive program, build skills across modern AI stacks, and embed directly with partner teams to ship real work. The first cohort, Claude Corps, is now launching in partnership with Anthropic with 1,000 fellows committed to deploy into nonprofits. The next chapter is enterprise, where the demand is larger, the budgets are real, and the urgency to build with AI is highest.
CodePath spent the past decade building this kind of infrastructure for education: training that produces engineers who perform at top companies, and ten years of outcomes data to prove it works. AI Corps takes the model to enterprise. The first cohort will prove the model inside mission\-driven organizations, and enterprise is the next chapter and what our Founding Product Manager, AI Corps will own.
The platform is already in active build, on track for a September launch, and it has been engineering\-led from day one: no product leadership, no customer validation, no feedback loops. Bringing those is this job, and getting design ahead of engineering is the first order of business.
Your ownership of the platform will power the full lifecycle: how organizations identify the AI capabilities they need, how fellows are trained to those specs and matched to partners, how they embed alongside existing teams, how incumbent employees build the skills to work with them, and how outcomes get measured in ways enterprise buyers act on.
The enterprise market is our clearest near\-term path to making CodePath financially self\-sustaining. Companies are racing to retrain entire departments for AI\-native work, corporate L\&D budgets are expanding, and almost no provider can prove the depth, rigor, or ROI that CodePath has spent a decade building. The path from tens of thousands today to millions of learners runs directly through this product, and the revenue opportunity is the largest in CodePath's history.
You will partner directly with Earned Revenue, Curriculum, and Engineering, and you will have unusual freedom to do it: a green\-lit, funded initiative already in motion, frontier AI tools with effectively unlimited Claude credits, and a small engineering team that ships faster than groups ten times its size.
Two things to know before you apply
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Quality is your scoreboard. Revenue here flows through partnerships, so you will not own a number. What you own is whether the platform earns that revenue: fellow engagement, student satisfaction, the quality of every partner and host organization touchpoint. If the experience is excellent, the business follows. If it is not, nothing else matters.
The ceiling is enormous. Through our partnership with Anthropic and our standing with universities, states, and employers, this product launches with distribution most startups spend a decade building. We need someone who thinks at that scale from day one.
What you'll do
The Senior Director of AI Programs owns the design and delivery of AI Corps programs. You own the platform that powers them: a new build, separate from CodePath's core learning platform, which has its own PM. In practice, that means:
- Define and own the AI Corps platform roadmap, turning fellow, partner, and program needs into clear priorities, holding a high bar for design quality across every fellow and partner touchpoint
- Define and own the metrics that prove the platform works: fellow engagement, student NPS, host organization satisfaction, and experience quality. Revenue is the outcome; these are the inputs you control
- Work directly with Anthropic teams and other enterprise partners on deployment, tooling, and joint enterprise opportunities
- Build the platform that makes AI Corps repeatable at enterprise scale, covering partner onboarding, fellow matching and deployment, performance tracking, and the full partner lifecycle
- Design the incumbent employee training product, working with AI Programs and Curriculum to build an AI enablement path for existing enterprise employees that runs alongside the fellow deployment model
- Run sharp discovery with enterprise partners and internal teams, then translate it into success metrics, prototypes, and shipped features
- Work closely with Earned Revenue to translate commercial needs into platform direction and ensure the product supports what the sales team needs to close and retain partners
- Design experiments to test your biggest bets, and use both qualitative signal and hard data to change course fast
- Be the connective tissue between Earned Revenue, AI Programs, Curriculum, and Engineering: align priorities, surface tradeoffs, and unblock the build
- Use AI across your entire workflow to compress weeks into days, raising the quality and the speed of what you ship
Who you are
You are a founding\-caliber PM who has built from nothing and stayed to scale it. AI is woven into how you work, and the size of this opportunity energizes you.
Required
- You have built 0 to 1 and stayed past it. You have taken a product from a blank page to real commercial scale, and you stayed through the hypergrowth that followed, so you know what comes after launch. Bonus if that was at a company that went from a handful of people to a billion\-dollar\-plus business
- AI is how you work every day. You can show, not just claim, how your workflow has changed: prototypes, requirements, and analyses you generate and pressure\-test in hours, not months
- You hold strong opinions and you can defend them live. You bring clear, well\-reasoned bets and stand behind them under pressure
- You thrive in ambiguity. You can structure messy problems, build alignment across commercial and technical teams, and drive execution with no playbook
- You have worked shoulder to shoulder with Sales or Customer Success, and you know what a deal\-blocking product gap looks like
- You have strong analytical instincts. You define the metrics that matter and read the data to make the call
- You write requirements engineers trust, and you can sell a product strategy to technical and non\-technical audiences alike
Preferred
- Background building for or selling to corporate L\&D, HR, or workforce and benefits buyers
- Fluency across the modern PM toolkit: product analytics (Mixpanel, Amplitude, Hex), prototyping and design (Figma, Framer), data querying (SQL), and AI\-assisted development tools (Claude Code, Codex, Cursor, or similar)
- Experience with talent marketplace, staffing, workforce deployment, or HR technology products
- Experience with enterprise SaaS platforms, integrations, or admin tooling
- Founder experience or equivalent time building in a zero\-to\-one environment
We encourage you to apply even if you do not meet every qualification listed. Strong candidates often look different from what a job description imagines, and we would rather talk to someone exceptional who checks seven of nine boxes than miss them entirely.
Compensation
CodePath has standardized salaries based on the position’s level, no matter where you live. For this role, we’re hiring for an Individual Contributor level position at an annual base salary of $135,000 to $175,000\. Total compensation is $200,000 to $232,000, which includes base salary plus a guaranteed monthly supplement. Salary is determined based on your relevant experience and skills as evaluated through our interview process.
Full\-Time Employee Benefits
This is a 100% remote position—work from anywhere in the U.S.! CodePath prioritizes employee well\-being with a competitive benefits package to support your health, financial security, and work\-life balance.
- Health \& Wellness: Medical, dental, and vision insurance (90% employer\-covered for employees and dependents), employer\-funded healthcare reimbursement, FSAs, and Employee Assistance Program
- Financial Security: 401(k), employer\-paid life \& disability insurance, and identity theft protection
- Work\-Life Balance: Generous PTO, paid holidays, 10 weeks of fully paid parental leave, and an annual year\-end company closure (Dec 24 – Jan 2\)
- Professional Growth: $1,000 annual professional development stipend and home office setup support
- Student Loan Forgiveness: CodePath is a qualifying employer for Public Service Loan Forgiveness (PSLF), helping employees manage student loan debt
- Additional Perks: Pet wellness plans, legal services, home/auto insurance discounts, and exclusive marketplace savings
Pay range
$200,000 \- $232,000 USD
Salary Context
This $135K-$232K range is below the median 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 CodePath.org, 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 $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 ($183K) sits 14% below the category median. Disclosed range: $135K to $232K.
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.
CodePath.org AI Hiring
CodePath.org has 1 open AI role right now. They're hiring across AI Product Manager. Based in Remote, US. Compensation range: $232K - $232K.
Remote Work Context
Remote AI roles pay a median of $170,000 across 1,926 positions. About 15% of all AI roles offer remote work.
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.
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