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Position:
Sr Product Manager \- AI Platform
Job Description:
We are seeking a visionary Senior Product Manager to lead the strategy, development, and execution of our next\-generation AI\-First Platform. This is a unique opportunity to help define and build a new platform from the ground up—one that fundamentally reimagines how customers interact with data, intelligence, applications, and workflows across the electronics ecosystem.
The platform will move beyond traditional SaaS experiences by empowering users to create personalized workspaces, configure applications, orchestrate workflows, and leverage AI Agents to drive business outcomes. Rather than simply providing software features, the platform will enable customers to build their own experiences, automate decisions, and connect intelligence directly into their daily workflows.
This role requires a strategic product leader who combines deep platform thinking, AI product expertise, customer obsession, and execution excellence. You will work across Product, Engineering, AI, Design, Customer Success, Sales, and Executive Leadership to define and deliver a category\-defining platform that serves as the foundation for the companys future growth.
What Youll Be Doing:
Define the Future of the Platform
- Own the vision, strategy, and roadmap for the companys AI\-First Platform, aligning platform investments with customer outcomes and business objectives.
- Lead the transformation from traditional applications to an AI\-native platform that enables users to interact through agents, workflows, automation, and configurable experiences.
- Establish a long\-term vision for how customers create personalized experiences, build configurable applications, and automate business processes on the platform.
Discover Customer Problems and Opportunities
- Conduct deep customer discovery to understand workflows, pain points, jobs\-to\-be\-done, and emerging AI use cases.
- Translate customer and market insights into platform capabilities that can be leveraged across multiple personas, applications, and workflows.
- Identify opportunities where AI, automation, and intelligent workflows can create measurable customer value and competitive differentiation.
Deliver Business Outcomes
- Ensure platform capabilities enable customers to solve real business problems across design, compliance, procurement, supply chain, and operations workflows.
- Prioritize investments based on customer value, strategic differentiation, scalability, and business impact.
Lead Cross\-Functional Execution
- Partner closely with Engineering, AI, Architecture, UX, Sales, Marketing, and Customer Success to deliver high\-impact platform capabilities.
- Drive roadmap planning, prioritization, execution, and product launches.
- Establish success metrics and monitoring frameworks that measure adoption, engagement, business outcomes, and customer value realization.
What We Are Looking For:
- Bachelors degree in a technical field; MBA a plus
- 12 years of industry experience with a bachelor’s degree or 8 years of experience with an advanced degree
- Deep experience in the software industry, with AI data experience in the last 5 years a must\-have; supply chain industry experience a plus
- Demonstrated experience managing and leading high performing teams
- Experience defining shared software platform capabilities and managing portfolios of products across related workflows
- Strong strategic thinking combined with world\-class execution skills
- Ability to lead by influencing in all directions internal and external to an organization
- Comfortable navigating through ambiguity and making data\-drive trade\-off and prioritization decisions
- Exceptional communication skills with the ability to engage executives, partners, customers, teams, and colleagues
- Willingness to travel as required
Work Arrangement: Hybrid: 3 days in office/2 days work from home.
What’s In It For You :
At Arrow, we recognize that financial rewards and great benefits are important aspects of an ideal job. That’s why we offer competitive financial compensation, including various compensation plans and a solid benefits package.
- Medical, Dental, Vision Insurance
- 401k, With Matching Contributions
- Short\-Term/Long\-Term Disability Insurance
- Health Savings Account (HSA)/Health Reimbursement Account (HRA) Options
- Paid Time Off (including sick, holiday, vacation, etc.)
- Tuition Reimbursement
- Growth Opportunities
- And more!
Are you being referred to one of our roles? If so, ask your connection at Arrow about our Employee Referral Process!
Annual Hiring Range/Hourly Rate:
$121,300\.00 \- $237,523\.00
Actual compensation offer to candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level. The pay ratio between base pay and target incentive (if applicable) will be finalized at offer.
Location:
US\-MA\-Peabody, Massachusetts (Technology Dr)
Time Type:
Full time
Job Category:
Product Supplier Management
EEO Statement:
Arrow is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, gender, age, sexual orientation, gender identity, national origin, veteran or disability status. (Arrow EEO/AAP policy)
All Arrow job postings are for existing job vacancies.We anticipate this requisition will be open for a minimum of five days, though it may be open for a longer period of time. We encourage your prompt application.
In any materials you submit, you may redact or remove age\-identifying information such as age, date of birth, or dates of school attendance or graduation. You will not be penalized for redacting or removing this information.
Salary Context
This $121K-$237K range is below the median for AI Product Manager roles in our dataset (median: $191K across 155 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 3,824 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At Arrow Electronics, 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 518 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($179K) sits 16% below the category median. Disclosed range: $121K to $237K.
Across all AI roles, the market median is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $97,380; Mid: $160,000; Senior: $227,400; Director: $243,000; VP: $250,000.
Arrow Electronics AI Hiring
Arrow Electronics has 1 open AI role right now. They're hiring across AI Product Manager. Based in Peabody, MA, US. Compensation range: $237K - $237K.
Location Context
Across all AI roles, 16% (613 positions) offer remote work, while 3,187 require on-site attendance. Top AI hiring metros: New York (2,448 roles, $210,000 median); San Francisco (1,990 roles, $253,000 median); Los Angeles (1,686 roles, $189,000 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 3,824 open positions tracked in our dataset. By seniority: 119 entry-level, 1,813 mid-level, 1,472 senior, and 420 leadership roles (Director, VP, C-Level). Remote roles make up 16% of the market (613 positions). The remaining 3,187 roles require on-site or hybrid attendance.
The market median for AI roles is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($293,500 median, 31 roles); AI Safety ($274,200 median, 51 roles); Research Engineer ($260,000 median, 401 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 3,824 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,702), Data Scientist (281), AI Software Engineer (258). 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 (119) are outnumbered by mid-level (1,813) and senior (1,472) 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 420 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 16% of all AI roles (613 positions), with 3,187 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 $200,000. Top-quartile roles start at $253,000, 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $142,800. 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 (1,968 postings), Aws (1,203 postings), Azure (882 postings), Rag (877 postings), Gcp (735 postings), Prompt Engineering (587 postings), Pytorch (586 postings), Claude (554 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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