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### When you join Verizon
You want more out of a career. A place to share your ideas freely — even if they’re daring or different. Where the true you can learn, grow, and thrive. At Verizon, we power and empower how people live, work and play by connecting them to what brings them joy. We do what we love — driving innovation, creativity, and impact in the world. Our V Team is a community of people who anticipate, lead, and believe that listening is where learning begins. In crisis and in celebration, we come together — lifting our communities and building trust in how we show up, everywhere \& always. Want in? Join the \#VTeamLife.
What you’ll be doing...
As the Senior Manager of Verizon’s high\-bandwidth engine, you will spearhead the commercial strategy and P\&L for the critical fiber infrastructure and AI connectivity solutions powering the global AI revolution. In this high\-visibility role, you will have the autonomy to shape and drive the roadmap for Dark Fiber, Wave, eLine, and next\-generation AI\-centric infrastructure—transforming massive technical capacity into market\-leading managed solutions for hyperscalers, colocation providers, and Fortune 500 enterprises. You won't just track metrics; you will mobilize cross\-functional teams—bridging Engineering, Sales, and Marketing—to optimize low\-latency architectures, capture explosive market growth, and define the connectivity backbone of the future.
- Commercial Architect:Own the product P\&L, driving revenue through aggressive pricing strategies, capacity planning, and market\-leading positioning for AI infrastructure and high\-capacity Ethernet services.
- AI Infrastructure Strategist:Translate emerging AI trends—including distributed inferencing, GPU cluster networking, and east\-west traffic architectures—into scalable connectivity platforms and high\-throughput data movement solutions.
- GTM Powerhouse:Design and execute high\-velocity go\-to\-market plans and product launches that maximize enterprise adoption, dominate market share, and accelerate customer acquisition across the AI economy.
- Sales Force Multiplier:Partner with global sales leaders to ensure perfect product\-market fit, arming them with the high\-impact value propositions and sales enablement materials needed to win complex, high\-stakes enterprise and hyperscaler deals.
- Customer Value Visionary:Solve business\-critical problems by translating deep user research, AI data pipeline requirements, and commercial insights into "must\-have" features that enterprise customers are eager to fund.
- Data\-Driven Decision Maker:Command market analytics, competitive intelligence (across cloud, edge, and private AI), and customer feedback loops to pivot strategy and prioritize the roadmap for maximum ROI.
- Executive Influence:Act as a key bridge between senior Verizon leadership and C\-suite clients, delivering compelling narratives that align high\-level corporate strategy with real\-world customer mission\-critical objectives.
- KPI\-Led Leadership:Establish and champion the North Star metrics that keep cross\-functional engineering, operations, and business development teams tightly focused on delivering high\-impact, resilient networking products.
What we’re looking for...
You’ll need to have:
- Bachelor’s degree or four or more years of work experience.
- Six or more years of relevant experience required, demonstrated through one or a combination of work and/or military experience, or specialized training.
- Six or more years of high\-stakes experience leading complex business initiatives and product lifecycles from concept to execution, including five or more years of dedicated Product Management across AI infrastructure, cloud platforms, data center technologies, and high\-tech markets.
- Strong understanding of GPU networking requirements, high\-capacity traffic models (10G to 400G\+), distributed computing environments, and AI workload transport optimization.
- Proven track record of navigating high\-level collaborations with sales organizations, large\-scale cloud service providers, AI platform providers, and Fortune 500 clients to deliver mutual success.
- Deep expertise in P\&L ownership, return\-on\-investment (ROI) frameworks, and market strategy, with the ability to synthesize user research and market analysis into a winning product vision.
Even better if you have one or more of the following:
- Bachelor’s or Master’s in Marketing, Finance, or an MBA; or an advanced technical degree.
- Strong understanding of high\-performance networks, AI fabric architectures, or orchestration platforms used to support large\-scale AI workloads.
- Proven ability to conceptualize innovative services, analyze AI infrastructure economics, and justify "build vs. buy" decisions through rigorous business acumen.
- Expert in product portfolio management, pricing models, and packaging strategies, using product intuition and user empathy to solve business\-critical problems.
- Entrepreneurial self\-starter with a "professional presence" and the ability to motivate cross\-functional teams and influence at all executive levels.
- Skilled in Agile/Scrum methodologies and project management, with the communication chops to get stakeholders and customers excited about the future roadmap.
- Highly proficient in Google Suite to drive data\-backed prioritization and performance tracking.
- Proficiency in leveraging data, market analytics, and customer feedback loops to uncover market opportunities and drive informed, data\-backed prioritization decisions.
- Expert\-level ability to craft and deliver compelling storytelling, high\-impact presentations, and clear product visions for C\-suite audiences, analysts, and strategic partners.
If Verizon and this role sound like a fit for you, we encourage you to apply even if you don’t meet every “even better” qualification listed above.
### Where you’ll be working
In this hybrid role, you'll have a defined work location that includes working from home and a minimum of three days per week in the office, which will be set by your manager. Employees are responsible for maintaining compliance with hybrid work policies.### Scheduled Weekly Hours
40### Equal Employment Opportunity
Verizon is an equal opportunity employer. We evaluate qualified applicants without regard to veteran status, disability or other legally protected characteristics.
### Benefits and Compensation
Our benefits are designed to help you move forward in your career, and in areas of your life outside of Verizon. From health and wellness benefit options including: medical, dental, vision, short and long term disability, basic life insurance, supplemental life insurance, AD\&D insurance, identity theft protection, pet insurance and group home \& auto insurance. We also offer a matched 401(k) savings plan, up to 8 company paid holidays per year and up to 6 personal days per year, paid parental leave, adoption assistance and tuition assistance, plus other incentives, we’ve got you covered with our award\-winning total rewards package. Depending on the role, employees have the opportunity to receive compensation in the form of premium pay such as overtime, shift differential, holiday pay, allowances, etc. Newly hired employees receive up to 15 days of vacation per year, which grows with additional service. For part\-timers, your coverage will vary as you may be eligible for some of these benefits depending on your individual circumstances.
The salary will vary depending on your location and confirmed job\-related skills and experience. This is an incentive based position with the potential to earn more. For part\-time roles, your compensation will be adjusted to reflect your hours.
The annual salary range for the location(s) listed on this job requisition based on a full\-time schedule is: $140,500\.00 \- $245,000\.00\.
The annual salary range for the New York location(s) listed on this job requisition based on a full\-time schedule is: $140,500\.00 \- $245,000\.00\.
Salary Context
This $140K-$245K 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 Verizon, 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. This role's midpoint ($192K) sits 10% below the category median. Disclosed range: $140K to $245K.
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.
Verizon AI Hiring
Verizon has 7 open AI roles right now. They're hiring across AI/ML Engineer, AI Product Manager, AI Architect, Data Scientist. Positions span Irving, TX, US, Basking Ridge, NJ, US. Compensation range: $188K - $275K.
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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