Interested in this AI Product Manager role at Charles Schwab?
Apply Now →About This Role
Austin, TX ; Westlake, TX ; Omaha, NE ; Raleigh, NC
Requisition ID 2026\-123082 Category Project Management, Product Management Position type Regular Pay range USD $105,600\.00 \- $175,000\.00 / Year Application deadline 2026\-06\-23
Your opportunity
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At Schwab, you’re empowered to make an impact on your career. Here, innovative thought meets creative problem solving, helping us “challenge the status quo” and transform the finance industry together.
We believe in the importance of in\-office collaboration and fully intend for the selected candidate for this role to work on site in the specified location(s).
Applicants must be currently authorized to work in the United States on a full\-time basis without employer sponsorship.
At Charles Schwab, we’re redefining how clients interact with digital experiences—using AI, search, and conversational platforms to simplify complex financial decisions. You will join a high\-impact product team focused on Conversational AI, Enterprise Search, and Digital Support experiences across web and mobile. This includes chat, voice, search, and help content—all unified into a seamless client journey.
This role sits at the intersection of strategy, execution, and innovation. You will shape the future of AI\-powered client experiences while ensuring operational excellence, scalability, and compliance. You will partner across product, engineering, data, design, risk, and service teams to deliver experiences that are intuitive, reliable, and high quality.
ResponsibilitiesProduct Strategy \& Execution* Define and execute product strategy across Conversational AI, Search, and Digital Support experiences
- Translate strategy into clear PRDs, roadmaps, and prioritized backlogs
- Maintain a continuous pipeline of delivery\-ready work across multiple sprints
- Balance near\-term delivery with long\-term platform evolution
AI Product Development (Modern Capability Required)* Drive development of AI\-powered experiences including LLM\-based, deterministic AI, and hybrid systems
- Establish and improve AI quality frameworks (evaluation, accuracy, grounding, hallucination mitigation)
- Partner with risk and compliance to ensure AI safety, governance, and responsible use
- Leverage experimentation, transcripts, and analytics to continuously improve experiences
Execution Excellence \& Release Management* Own end\-to\-end product lifecycle, including planning, development, testing, release, and post\-launch optimization
- Lead release management practices, including release notes, readiness, and stakeholder communication
- Ensure strong quality assurance and production stability across features
- Maintain documentation across product, operational, and system workflows
Cross\-Functional Leadership* Lead cross\-functional alignment across product, engineering, design, risk, compliance, and operations
- Influence stakeholders and drive decisions across multiple levels of leadership
- Champion Agile practices including sprint planning, backlog refinement, and demos
Executive Communication \& Storytelling (Elevated Expectation)* Create and deliver executive\-ready presentations that clearly communicate strategy, progress, risks, and outcomes
- Simplify complex AI and technical concepts into clear narratives for leadership audiences
- Provide consistent visibility into product performance, roadmap, and key decisions
Hands\-on Product \& Technical Fluency* Demonstrate “vibe coding” and rapid prototyping ability to explore ideas and accelerate delivery
- Work closely with engineering to define technical approaches, trade\-offs, and implementation details
- Contribute to tool selection and product workflows across the team
What You Care About* Delivering high\-quality, intuitive client experiences that solve real problems
- Building trustworthy AI systems that are safe, compliant, and reliable
- Driving outcomes over output, with measurable client and business impact
- Creating clarity across ambiguity and aligning teams around shared goals
- Developing strong partnerships across product, engineering, and business stakeholders
- Maintaining operational excellence, system resiliency, and scalable processes
- Continuously improving through data, experimentation, and client feedback
- Staying current on emerging trends in AI and digital experiences
What you have
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Required Qualifications
Core Product \& Leadership Experience* 5\+ years of digital product management experience
- Experience delivering complex digital platforms across web and mobile
- Strong ability to influence stakeholders and drive alignment across organizations
- Agile experience (Scrum, backlog management, sprint planning)
AI \& Technical Capabilities* Experience with conversational AI, search, chatbots, voice, or machine learning\-driven products
- Working knowledge of GenAI, LLMs, and AI system design principles
- Ability to evaluate and improve AI quality, performance, and safety
- Comfort working with technical teams on architecture, integrations, and data
Product Craft \& Discipline* Strong experience writing product requirement documents (PRDs) and defining clear acceptance criteria
- Experience with release management, lifecycle ownership, and product operations
- Ability to translate strategy into actionable roadmaps and execution plans
Communication \& Executive Presence* Excellent presentation and storytelling skills, with experience presenting to senior leadership
- Ability to communicate complex concepts clearly across technical and non\-technical audiences
- Strong written communication and documentation skills
Preferred Qualifications
- Strong organizational skills with the ability to manage multiple priorities
- Self\-starter mindset with a bias toward action and continuous improvement
- Documented “vibe coding” and rapid prototyping experience
In addition to the salary range, this role is also eligible for bonus or incentive opportunities.What’s in it for you
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At Schwab, you’re empowered to shape your future. We champion your growth through meaningful work, continuous learning, and a culture of trust and collaboration—so you can build the skills to make a lasting impact. Our Hybrid Work and Flexibility approach balances our ongoing commitment to workplace flexibility, serving our clients, and our strong belief in the value of being together in person on a regular basis.
We offer a competitive benefits package that takes care of the whole you – both today and in the future:
- 401(k) with company match and Employee stock purchase plan
- Paid time for vacation, volunteering, and 28\-day sabbatical after every 5 years of service for eligible positions
- Paid parental leave and family building benefits
- Tuition reimbursement
- Health, dental, and vision insurance
### Share:
- X
Eligible Schwabbies receive
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- Medical, dental and vision benefits
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- 401(k) and employee stock purchase plans
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- Tuition reimbursement to keep developing your career
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- Paid parental leave and adoption/family building benefits
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- Sabbatical leave available after five years of employment
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Salary Context
This $105K-$175K range is in the lower quartile for AI Product Manager roles in our dataset (median: $187K across 164 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 4,133 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At Charles Schwab, 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 610 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($140K) sits 34% below the category median. Disclosed range: $105K to $175K.
Across all AI roles, the market median is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Safety ($274,200) and AI Engineering Manager ($268,700). By seniority level: Entry: $97,760; Mid: $165,778; Senior: $227,400; Director: $250,000; VP: $250,000.
Charles Schwab AI Hiring
Charles Schwab has 6 open AI roles right now. They're hiring across AI Product Manager, AI/ML Engineer, Data Scientist. Positions span Austin, TX, US, Westlake, TX, US, Southlake, TX, US. Compensation range: $94K - $247K.
Location Context
AI roles in Austin pay a median of $215,300 across 535 tracked positions. That's 7% above 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 4,133 open positions tracked in our dataset. By seniority: 106 entry-level, 1,901 mid-level, 1,663 senior, and 463 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (583 positions). The remaining 3,532 roles require on-site or hybrid attendance.
The market median for AI roles is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Safety ($274,200 median, 57 roles); AI Engineering Manager ($268,700 median, 42 roles); Research Engineer ($260,000 median, 442 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 4,133 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,865), Data Scientist (339), AI Software Engineer (313). 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 (106) are outnumbered by mid-level (1,901) and senior (1,663) 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 463 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (583 positions), with 3,532 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 $200,700. Top-quartile roles start at $254,000, 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 Safety roles lead at $274,200 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 (2,128 postings), Aws (1,324 postings), Azure (1,003 postings), Rag (916 postings), Gcp (817 postings), Pytorch (655 postings), Prompt Engineering (639 postings), Claude (571 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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