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Principal Product Manager (BD\-PM in AI \& Data Center Infrastructure)
Date: Jun 4, 2026
Location: San Jose, California, United States
Company: Super Micro Computer
Job Req ID: 29187
About Supermicro:
Supermicro® is a Top Tier provider of advanced server, storage, and networking solutions for Data Center, Cloud Computing, Enterprise IT, Hadoop/ Big Data, Hyperscale, HPC and IoT/Embedded customers worldwide. We are the \#5 fastest growing company among the Silicon Valley Top 50 technology firms. Our unprecedented global expansion has provided us with the opportunity to offer a large number of new positions to the technology community. We seek talented, passionate, and committed engineers, technologists, and business leaders to join us.Job Summary:
We are seeking a commercially driven leader to own and accelerate the market growth of our Datacenter Building Block Solutions (DCBBS). This senior role is fundamentally a business development position with product strategy ownership. Your primary mission is to directly secure major design wins, close large\-scale strategic deals, and drive the commercial adoption of our rack\-scale and AI\-optimized infrastructure solutions. You will combine deep technical expertise with sharp commercial acumen to architect winning customer solutions and translate them into measurable revenue growth. Essential Duties and Responsibilities:
- Own Commercial Execution \& Market Penetration: Directly drive the adoption and revenue growth of the DCBBS portfolio. Lead the pursuit and closure of complex, high\-value strategic deals with large enterprises and hyperscale customers. Develop and execute targeted account and partner strategies for net\-new logo acquisition.
- Lead End\-to\-End Solution Development for Deal Closure: Translate customer business needs and technical workload requirements (AI/HPC, etc.) into compelling, customized DCBBS proposals. Architect total solutions—encompassing GPU platforms, power, cooling, and cluster design—to win strategic bids and secure long\-term design wins.
- Define Market\-Backed Product Strategy: Shape the product vision and roadmap based on direct field intelligence, competitive analysis, and a proven understanding of what drives customer purchasing decisions in data center infrastructure. Prioritize initiatives that deliver clear competitive advantage and address immediate market opportunities.
- Cultivate \& Manage Strategic Executive Relationships: Build and leverage multi\-threaded, executive\-level relationships with key decision\-makers at target accounts and ecosystem partners. Act as a strategic advisor to influence long\-term infrastructure plans and position Supermicro as the preferred integrated solutions provider.
- Champion Cross\-Functional GTM Leadership: Orchestrate Engineering, Sales, Rack Integration, and Sales Engineering teams to align product development with market demand and ensure flawless execution of strategic deals from qualification through to delivery.
Qualifications:
+ Education: Bachelor’s degree in Computer Engineering, Electrical Engineering, Business Administration, or a related technical field. MBA or advanced degree is a strong plus.
+ Experience:
- 15\+ years in a hybrid role with significant, direct business development, technical sales, or strategic account management responsibility within data center/AI infrastructure.
- Hands\-on experience and deep technical knowledge of data center infrastructure (power, cooling, rack integration) is preferred.
- Must possess comprehensive expertise in AI/HPC server architecture, key technologies (GPU platforms, InfiniBand, high\-speed networking), and associated workload requirements.
+ Skills:
- Outstanding commercial negotiation and executive presentation skills, with the ability to articulate business value and craft winning proposals.
- Strategic thinker with a results\-oriented mindset, focused on market penetration and revenue growth.
- Adept at leveraging market data, competitive intelligence, and customer feedback to drive both product and sales strategy.
- A self\-motivated driver who thrives in a dynamic, cross\-functional environment and is measured by commercial outcomes.
Salary Range
$200,000 \- $230,000
The salary offered will depend on several factors, including your location, level, education, training, specific skills, years of experience, and comparison to other employees already in this role. In addition to a comprehensive benefits package, candidates may be eligible for other forms of compensation, such as participation in bonus and equity award programs.EEO Statement
Supermicro is an Equal Opportunity Employer and embraces diversity in our employee population. It is the policy of Supermicro to provide equal opportunity to all qualified applicants and employees without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veteran status or special disabled veteran, marital status, pregnancy, genetic information, or any other legally protected status.
Salary Context
This $200K-$230K range is above 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 Super Micro Computer, Inc., 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 583 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. Disclosed range: $200K to $230K.
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.
Super Micro Computer, Inc. AI Hiring
Super Micro Computer, Inc. has 2 open AI roles right now. They're hiring across AI Product Manager. Based in San Jose, CA, US. Compensation range: $211K - $230K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 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 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.
Frequently Asked Questions
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