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About MISUMI Americas
MISUMI Americas, a division of MISUMI Group, is a leading provider of standard, configurable, and custom manufacturing solutions. By integrating a vast catalog of components with a world\-class digital manufacturing platform, MISUMI Americas empowers engineers and procurement teams to accelerate innovation across the entire product lifecycle. With operations in the San Francisco Bay Area and Chicago, the company serves as a vital partner for the most innovative companies in the Americas.
Impact In This Role
As our Principal Product Manager \- AI \& Intelligent Manufacturing Systems, you'll serve as a strategic and technical thought leader driving the vision, roadmap, and execution of AI\-powered capabilities across MISUMI Americas Manufacturing Quoting and Fulfillment Platform. This is a highly visible, high\-leverage role — one that shapes how AI and automation become foundational to MISUMI Americas operating system for new product development (NPD). You'll partner directly with our AI R\&D, data science, and platform architecture teams to define the core intelligence layer that powers quoting, supply orchestration, and manufacturing decision\-making at scale.
You will own and evolve the product strategy that fuses advanced AI models, data\-driven automation, and manufacturing domain intelligence into a cohesive system that sets new standards for operational efficiency, precision, and speed.
This role is ideal for a seasoned product leader with experience bringing AI\-first enterprise platforms to life — someone equally comfortable discussing model architectures and data pipelines as they are business value and market differentiation.
You will report to the VP, Product Management.
Areas of Responsibility:
### 1\. AI Technology Strategy \& Product Vision
- Define the long\-term AI technology strategy for MISUMI Americas digital manufacturing platform — including where and how to leverage LLMs, machine learning, computer vision, and reinforcement learning
- Partner with AI research and engineering leadership to translate R\&D advances into scalable, customer\-facing capabilities
- Identify and prioritize core AI product opportunities — from intelligent quoting and auto\-classification of 3D models to predictive supplier matching and adaptive routing engines
- Drive the architectural vision for MISUMI Americas AI intelligence layer, ensuring alignment between data infrastructure, ML systems, and platform integration
- Evangelize the role of AI within the organization — educating teams on capabilities, limitations, and ethical deployment of intelligent systems
### 2\. Deep Technical Product Leadership
- Serve as the product owner for AI infrastructure and model lifecycle management, including data acquisition, training, deployment, monitoring, and feedback loops
- Partner with ML engineers and data scientists to design human\-in\-the\-loop workflows that continuously improve system accuracy and explainability
- Own the AI feature pipeline: define use cases, establish model performance metrics (precision, recall, latency, cost), and measure impact on business KPIs (quote accuracy, margin, lead time)
- Collaborate with platform engineering to ensure scalability, modularity, and compliance in AI integrations
- Drive responsible AI practices, including fairness, transparency, and auditability in model\-driven decision systems
### 3\. Solutions Integration \& Application Development
- Lead the development of AI\-driven application modules — such as automated quoting, manufacturability assessment, supplier recommendation, and production forecasting
- Work with product teams across quoting, fulfillment, and partner management to identify where intelligence adds differentiated value
- Ensure AI and automation capabilities are embedded seamlessly into MISUMI Americas core user experiences and operational workflows
- Act as a bridge between AI technology development and solution commercialization, ensuring innovations move efficiently from lab to production
### 4\. Metrics, Experimentation, and Validation
- Define the performance framework for all AI\-enabled systems, including model metrics (accuracy, throughput, latency), business KPIs (margin improvement, cycle time reduction), and adoption metrics
- Lead data\-informed experimentation programs to validate new model capabilities and measure real\-world impact before scaling
- Champion continuous learning loops between R\&D, product, and operations teams
### 5\. Cross\-Functional \& Executive Influence
- Partner with senior leadership across Product, Engineering, Data, and Operations to align AI investments with strategic business outcomes
- Influence architecture, resource allocation, and data strategy decisions that affect MISUMI Americas AI roadmap
- Mentor and guide other product managers in the organization on AI\-first thinking and technical product management best practices
- Represent MISUMI Americas externally — at conferences, customer forums, and AI ecosystem events — as a thought leader in intelligent manufacturing systems
Experience/Qualifications:
### Required
- 10\+ years of product management experience, including 4\+ years leading AI or ML\-driven products from research to production
- Startup experience with demonstrated 0\-to\-MVP\-to\-1 product ownership; ideally at a company that achieved a successful exit (acquisition or IPO)
- Proven track record building AI\-first SaaS or enterprise systems, ideally in manufacturing, supply chain, logistics, or industrial automation
- Deep understanding of AI technologies, including LLMs, supervised/unsupervised ML, computer vision, or predictive analytics pipelines
- Demonstrated success collaborating with AI research teams and data engineering to operationalize models into scalable, production\-grade systems
- Fluency in data infrastructure concepts (feature stores, inference APIs, model retraining, observability)
- Strong technical intuition and ability to engage deeply with engineers and data scientists on architecture, experimentation, and trade\-offs.
- Analytical rigor and comfort with experimentation frameworks, A/B testing, and quantitative product measurement
- Exceptional communication and influence skills — able to connect technical complexity to business impact and inspire alignment across functions
### Preferred
- Domain experience in manufacturing, supply chain, or CAD/CAM ecosystems
- Experience designing or managing systems with human\-in\-the\-loop AI, active learning, or automated decision\-support models
- Working knowledge of product data ontologies, graph databases, or knowledge modeling for industrial applications
- Track record of thought leadership or published work on AI strategy, ML productization, or applied AI ethics
Physical Demands
The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
While performing the duties of this job, the employee routinely is required to sit; walk; talk and hear; use hands to keyboard, fingers, handle, and feel; stoop, kneel, crouch, twist, crawl, reach, and stretch.
### Perks and Benefits
- Competitive medical, dental, and vision insurance
- 401K plan
- Parental leave programs
- Paid volunteer days
- And much, much more!
MISUMI Americas is continuing to expand our remote US workforce. Applicants from the following states are eligible to apply:
Arizona (AZ), California (CA), District of Columbia, (DC), Delaware (DE), Florida (FL), Georgia (GA), Hawaii (HI), Iowa (IA), Illinois (IL), Indiana (IN), Kansas (KS), Massachusetts (MA), Maryland (MD), Michigan (MI), Minnesota (MN), Missouri (MO), North Carolina (NC), New Hampshire (NH), New Jersey (NJ), New York (NY), Nevada (NV), Ohio (OH), Oregon (OR), South Carolina (SC), Texas (TX), Tennessee (TN), Utah (UT), Virginia (VA), Washington (WA), West Virginia (WV), Wisconsin (WI), Wyoming (WY)
Salary Range: $210,000 to $230,000 per year, based upon experience
Interested in learning more? We look forward to hearing from you soon.
We're actively seeking teammates who:
- Bring diverse perspectives and experience to our culture and company.
- Excel at being part of a strong, empathetic team.
- Thrive in an environment emphasizing respect, honesty, collaboration, and growth.
- Have an 'always learning' mindset that celebrates learning, not just wins.
- Help us continue to build a world\-class organization that values the contributions of all of our teammates
We encourage applications from members of underrepresented groups, including but not limited to women, members of the LGBTQ community, people of color, people with disabilities, and veterans.
Salary Context
This $210K-$230K range is above the 75th percentile for AI Product Manager roles in our dataset (median: $188K across 140 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 3,708 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At Fictiv, 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 $216,175 based on 270 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. Disclosed range: $210K to $230K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Fictiv AI Hiring
Fictiv has 2 open AI roles right now. They're hiring across AI Product Manager, AI/ML Engineer. Based in Oakland, CA, US. Compensation range: $230K - $260K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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