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Job Description
Product Manager / Product Builder AI Incubation
Job Location: San Jose, California, San Jose. California
Location Flexibility: Primary Location Only
Req Id: 11074
Posting Start Date: 8/10/26
At Fujitsu, our purpose is to make the world more sustainable by building trust in society through innovation. Founded in Japan in 1935, Fujitsu has been a pioneer in technology and innovation for decades. Today, as a world\-leading digital transformation partner, we are committed to transforming business and society in the digital age.
With approximately 130,000 employees across over 50 countries, Fujitsu offers a broad range of products, services, and solutions. We collaborate with our customers to co\-create solutions that drive enterprise\-wide digitalization while actively working to address social issues and contribute to the United Nations Sustainable Development Goals (SDGs).
Product Manager / Product Builder AI Incubation
We are an AI incubation team within Fujitsu’s Global Technology Strategy Unit, turning research breakthroughs and early customer signals into enterprise\-ready AI products. Our work spans applied AI systems including workload orchestration, vision, agentic systems. This is a hands\-on product\-builder role on a small team. You will own the messy middle between research and revenue : shaping early technical capabilities into clear product direction, validating them with customers, driving rapid productization, and helping launch the first enterprise deployments.
This is not a spec\-writing\-only PM role. You may be defining product strategy one day, shaping a customer demo the next, writing a launch deck, aligning engineers and researchers, or helping technical sales land the first design partner. If you want ownership from research handoff to real customer impact , this role is built for you.
What you’ll own
- Define product vision, MVP scope, and roadmap for emerging AI capabilities coming out of research.
- Translate prototypes, PoCs, and early IP into clear product direction, customer value, and launch plans.
- Identify wedge use cases, target customers, GTM narrative, and first revenue opportunities.
- Partner closely with research, engineering, technical sales, solution architects, and business stakeholders.
- Shape early customer engagements including demos, PoCs, deal support, deployment planning, and production\-readiness tradeoffs.
- Drive rapid productization cycles, moving from early signal to launch\-ready product within months.
- Create the artifacts that move work forward: product briefs, requirements, demo narratives, decks, documentation, positioning, and internal decision docs.
- Incorporate customer feedback and prepare products for handoff to scaling business units.
What we’re looking for
- 5–8\+ years in product management, technical product management, product builder, founder, or similar roles.
- Strong technical foundation in AI/ML, computer science, engineering, data science, robotics, physics, or equivalent hands\-on technical experience.
- Working fluency with modern AI systems, such as generative AI, agents, VLMs, model serving, ML workflows, AI infrastructure, or applied AI products.
- Experience turning ambiguous technical capabilities into product direction, MVP scope, customer value, and launch plans.
Proven 0* 1 or research\-to\-product experience in fast\-moving, ambiguous environments.
- Experience with enterprise customers, including PoCs, pilots, deployments, production rollouts, or technical sales collaboration.
- Strong communication across research, engineering, sales, executives, and customers.
- Comfort operating lean and hands\-on, without relying on a large supporting product, PMM, or sales enablement org.
Strong pluses
- PhD, Master’s, or equivalent deep technical experience in AI/ML, computer science, engineering, robotics, physics, or related fields.
- Business\-level Japanese, especially for collaboration with global research, engineering, and business teams.
- Startup, founder, or founding\-team experience where you personally drove product, customer discovery, and early GTM.
- Top\-tier strategy consulting experience, if paired with hands\-on technical, product, or startup execution.
- Big tech experience launching AI, infrastructure, enterprise software, developer platform, or applied ML products.
- Experience bringing AI products from PoC to production in enterprise environments.
Why this role
- Direct access to frontier AI research, infrastructure, and emerging IP.
- Real ownership from product vision to customer validation, launch, and early revenue.
- A small team where your work visibly ships and materially shapes the product direction.
- Exposure across research, product, GTM, customer deployment, and global business stakeholders.
- An exciting opportunity to build AI products that move beyond demos into real enterprise environments.
\#Americas\_Priority
Relocation Supported: Yes
Visa Sponsorship Approved: No
At Fujitsu, we are committed to an inclusive recruitment process that values the diverse backgrounds and experiences of all applicants. We believe that hiring people from a wide variety of backgrounds makes us stronger, not because it's the right thing to do, but because it allows us to draw on a wider range of perspectives and life experiences.
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 4,317 AI roles we're tracking, AI Product Manager positions make up 4% of the market. At Fujitsu, 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 $217,100 based on 471 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Fujitsu AI Hiring
Fujitsu has 3 open AI roles right now. They're hiring across AI Product Manager, AI/ML Engineer. Positions span San Jose, CA, US, New York, NY, US, Dallas, TX, US. Compensation range: $180K - $180K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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