Interested in this AI Product Manager role at WeRide.ai?
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Established in 2017, WeRide (NASDAQ: WRD) is a leading global commercial-stage company that develops autonomous driving technologies from Level 2 to Level 4 and is the world's first publicly listed autonomous vehicle (AV) company. Its business footprint now spans more than 60 cities across 13 countries. Powered by the intelligent, versatile, and highly adaptable WeRide One platform, the company provides autonomous driving products and services ranging from Level 2 to Level 4, addressing mobility, logistics, and urban services.
WeRide builds Physical AI solutions for advanced AI and robotic systems, including ready-to-deploy capability stacks, purpose-built hardware, and customized solution programs.
We are looking for a high-agency, hands-on business developer who can open accounts and personally close complex technical deals. This is a quota-carrying individual contributor role, not a people-management position. You will own registered accounts from first contact through discovery, paid pilot, contract, delivery, collection, and expansion.
What We Sell:
- Ready-to-deploy Physical AI solutions: licensable capability stacks organized by task, environment, modality, quality, and permitted use.
- Purpose-built hardware: wearable and environment-specific systems combining sensors, synchronization, calibration, field tooling, and support.
- Customized solution services: programs covering scenario design, integration, quality assurance, delivery, evaluation, and ongoing support.
What You Will Own:
- Build pipeline through existing relationships, targeted outbound, referrals, events, and partners.
- Secure direct access to technical champions, executive sponsors, and economic buyers.
- Lead technical and commercial discovery and translate customer needs into clear offers.
- Convert qualified demand into paid pilots with measurable acceptance criteria and expansion paths.
- Own pricing, proposals, negotiation, contracts, forecasting, close, collection, and account growth.
- Carry a personal revenue target and maintain discipline on qualification, discounting, margin, and payment terms.
- Keep account ownership, activity, pipeline, and next steps current in the CRM.
- Coordinate internal technical and delivery teams while bringing market feedback back to product.
Qualifications:
- 6+ years in enterprise technical sales, business development, strategic accounts, or a comparable commercial role.
- 3+ years selling into robotics, embodied AI, autonomy, sensors, computer vision, or related infrastructure.
- Existing relationships with relevant technical and commercial decision-makers and the ability to reach them directly.
- A record of personally opening accounts, winning paid pilots, closing contracts, and expanding revenue.
- Strong commercial judgment across qualification, pricing, negotiation, procurement, contracts, margin, and collections.
- Excellent written and verbal English and the ability to operate independently in an early-stage environment.
Technical Fluency & Travel Requirement:
- You do not need to be an ML engineer, but you must be credible with technical buyers. You should understand common sensor modalities, synchronization and calibration, system integration and QA, long-tail failures, domain gaps, safety and operational constraints, acceptance criteria, and solution usage rights—and how they affect scope, cost, delivery risk, and commercial value.
- This role is remote within the United States, with a preference for candidates based in the San Francisco Bay Area or able to spend meaningful time there. Travel of approximately 30–50% is expected for customer meetings, onsite programs, industry events, and partner engagement.
Your base pay is one part of your total compensation package. For this position, the reasonably expected pay range is between $160,000 - $230,000 for the level at which this job has been scoped. Your base pay will depend on several factors, including your experience, qualifications, education, location, and skills. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for an annual performance bonus, equity, and a competitive benefits package. WeRide.ai offers competitive salary depending on the experience. Employee benefits include: Premium Medical, Dental and Vision Plan (No cost from employees or their families) Free Daily Breakfast, Lunch and Dinner Paid vacations and holidays 401K plan
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Salary Context
This $160K-$230K range is above the median for AI Product Manager roles in our dataset (median: $194K across 123 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 9,079 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At WeRide.ai, 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 $220,200 based on 947 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $229,300. This role's midpoint ($195K) sits 11% below the category median. Disclosed range: $160K to $230K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
WeRide.ai AI Hiring
WeRide.ai has 1 open AI role right now. They're hiring across AI Product Manager. Based in San Jose, CA, US. Compensation range: $230K - $230K.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 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 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 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 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. 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 $256,000 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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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