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Company Overview
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At Motorola Solutions, we believe that everything starts with our people. We’re a global close\-knit community, united by the relentless pursuit to help keep people safer everywhere. We build and connect technologies to help protect people, property and places. Our solutions foster the collaboration that’s critical for safer communities, safer schools, safer hospitals, safer businesses, and ultimately, safer nations. Connect with a career that matters, and help us build a safer future.
Department Overview
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Within the Video Security \& Access Control (VS\&AC) business unit at Motorola Solutions, we are helping solve some of the biggest challenges around safety and physical security by developing advanced artificial intelligence (AI) technologies and products. Avigilon, a Motorola Solutions brand, designs, develops, and manufactures advanced AI, video analytics, network video management software and hardware, and surveillance cameras that help change the way people interact with their security systems.
Job Description
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This is a high\-visibility, high\-impact leadership role responsible for leading one of the most critical pillars of the Avigilon system. Reporting directly to the Director, Product Management for Avigilon Platform , you will be the primary architect of our intelligence strategy, defining how AI transforms raw camera and sensor data into actionable security insights and workflows.
This is intended to be a hybrid individual contributor and people management role. While you will initially operate as a senior individual contributor with no direct reports, this role is positioned to scale, with the potential to manage a small team of Product Managers in the future.
What You’ll Do
- Lead AI Strategy \& Vision: Define the multi\-year vision, strategy, and roadmap for AI and Analytics across the Avigilon platform.
- Define End\-to\-End Experiences: Architect what AI\-enabled experiences look like for our users—from initial detection on a device to forensic search and alerting within the video management or access control system.
- Drive Consistency: Partner closely with the Products teams for the Video Management Software, Access Control, Appliances, and Devices Product Management teams to ensure AI capabilities feel like cohesive and consistent experiences across Avigilon products rather than siloed features.
- Bridge Research and Engineering: Collaborate with AI Platform Engineering and AI Research teams to define detailed requirements for new features, making critical decisions on technical approaches and performance tradeoffs.
- Field Performance \& Advocacy: Act as a key stakeholder in addressing customer issues arising from AI performance in the field, working with engineering to tune and improve systems based on real\-world data.
- Master the Message: Partner with Product Marketing to ensure effective, consistent, and cohesive messaging for our AI capabilities, and ensure the delivery of high\-quality product collateral to explain them.
- Team Leadership \& Mentorship: Provide mentorship and guidance to other PMs across the platform team. As the AI function grows, you will be responsible for recruiting, hiring, and managing additional PM talent to support the roadmap.
Qualifications
- Experience: 7\+ years in Product Management, with a significant focus on AI/ML and a proven track record of leading complex, multi\-stakeholder product initiatives.
- AI/ML Domain Expertise: Deep understanding of AI, machine learning, and advanced video analytics, with the ability to engage credibly with research and engineering teams on architecture and tradeoffs.
- GenAI Proficiency: Hands\-on experience building or scaling products utilizing Large Language Models (LLMs) , Vision Language Models (VLMs), semantic search, or generative workflows.
- MCP Proficiency: Familiarity with Model Context Protocol (MCP) or similar frameworks for connecting AI models to secure, external data sources and tools.
- Systems Thinking: Ability to visualize how edge\-to\-cloud AI implementations affect the entire system, from camera bandwidth to user interface, or how a model change at the edge (camera) interacts with a GenAI agent in the cloud to produce a user\-facing insight.
- Influencing Skills: Exceptional ability to navigate a highly matrixed organization and gain trust with leaders across multiple layers without formal authority.
- Hybrid Leadership Mindset: Proven ability to act as a high\-level individual contributor while demonstrating the leadership skills to mentor and eventually manage a team of PMs.
- Communication: Exceptional written and oral communication skills, with the ability to translate complex technical concepts into compelling value propositions. Ability to "translate" between AI researchers and non\-technical stakeholders, ensuring technical complexity never compromises user experience.
What Sets You Apart
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- Agentic AI Experience: You have previously built or managed AI "agents" that perform multi\-step tasks or tool\-calling.
- Systems Experience Bridging Hardware and Software: Experience managing AI features that live across the "Edge\-to\-Cloud" spectrum.
- Security Domain Knowledge: A deep understanding of the physical security, video security, or access control landscapes.
Target Base Salary Range: $160,000 \- $200,000
Consistent with Motorola Solutions values and applicable law, we provide the following information to promote pay transparency and equity. Pay within this range varies and depends on job\-related knowledge, skills, and experience. The actual offer will be based on the individual candidate.
\#LI\-CA1
Basic Requirements
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- Bachelors Degree
- 7\+ years of experience in product management
- Legal authorization to work in the U.S. indefinitely is required. Employer work permit sponsorship is not available for this position
Travel Requirements
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Under 25%
Relocation Provided
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None
Position Type
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Experienced
Referral Payment Plan
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No
Our U.S. Benefits include:
- Incentive Bonus Plans
- Medical, Dental, Vision benefits
- 401K with Company Match
- 10 Paid Holidays
- Generous Paid Time Off Packages
- Employee Stock Purchase Plan
- Paid Parental \& Family Leave
- and more!
*EEO Statement*
Motorola Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion or belief, sex, sexual orientation, gender identity, national origin, disability, veteran status or any other legally\-protected characteristic.
We are proud of our people\-first and community\-focused culture, empowering every Motorolan to be their most authentic self and to do their best work to deliver on the promise of a safer world. If you’d like to join our team but feel that you don’t quite meet all of the preferred skills, we’d still love to hear why you think you’d be a great addition to our team.
We’re committed to providing an inclusive and accessible recruiting experience for candidates with disabilities, or other physical or mental health conditions. To request an accommodation, please complete this Reasonable Accommodations Form so we can assist you.
Salary Context
This $160K-$200K range is below 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 Motorola Solutions, 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. Mid-level AI roles across all categories have a median of $165,000. This role's midpoint ($180K) sits 16% below the category median. Disclosed range: $160K to $200K.
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.
Motorola Solutions AI Hiring
Motorola Solutions has 9 open AI roles right now. They're hiring across AI Product Manager, AI/ML Engineer, AI Software Engineer. Positions span Waltham, MA, US, MA, US, Los Angeles, CA, US. Compensation range: $155K - $290K.
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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