Interested in this AI Product Manager role at World Wide Technology?
Apply Now →Skills & Technologies
About This Role
Qualifications
- 5\+ years leading product teams or innovation\-focused initiatives.
- 5\+ years managing internal stakeholder or customer relationships.
- Experience enabling AI platforms (e.g., Microsoft Copilot, Power Automate, Azure AI, M365 Graph).
- Proven ability to translate AI vision into a practical execution roadmap.
- Experience deploying enterprise workflows, copilots, and automation in partnership with business teams.
- Strong background in requirements analysis, AI opportunity discovery, and prioritization methods.
- Understanding of prompt engineering, workflow agent configuration, and human\-in\-the\-loop patterns.
- Demonstrated ability to negotiate competing priorities using business value and ROI assessments.
- Familiarity with product analytics, adoption metrics, forecasting, and measurable outcomes.
- Experience developing user personas, journey maps, and digital experience frameworks.
- Excellent communication skills tailored for both technical and non\-technical audiences.
- Ability to drive complex initiatives across Engineering, PMO, Operations, and Innovation teams.
Desired Work Experience
- 5\+ years in AI product management, innovation management, or digital transformation.
- Experience building AI workflows, copilots, or enterprise automation solutions.
- Experience in an Agile software development environment.
- Experience supporting PMO, engineering, or enterprise operational teams.
- Bachelor's degree or 5\+ years of relevant professional experience.
- Experience in SaaS, data platforms, or automation/AI governance preferred.
The well\-being of WWT employees is essential. So, when it comes to our benefits package, WWT has one of the best. We offer the following benefits to all full\-time employees:
- Health and Wellbeing: Health, Dental, and Vision Care, Onsite Health Centers, Employee Assistance Program, Wellness program
- Financial Benefits: Competitive pay, Profit Sharing, 401k Plan with Company Matching, Life and Disability Insurance, Tuition Reimbursement
- Paid Time Off: PTO and Sick Leave (starting at 20 days per year) \& Holidays (10 per year), Parental Leave, Military Leave, Bereavement
- Additional Perks: Nursing Mothers Benefits, Voluntary Legal, Pet Insurance, Employee Discount Program
We strive to create an environment where all employees are empowered to succeed based on their skills, performance, and dedication. Our goal is to cultivate a culture of belonging that encourages innovation, collaboration, and respect for all team members, ensuring that WWT remains a great place to work for All!
Certain states and localities require employers to post a reasonable estimate of salary range. A reasonable estimate of the current base pay range for this position is $130,800 \- $163,500 annually. Actual salary will be based on a variety of factors, including shift, location, experience, skill set, performance, licensure and certification, and business needs. The range for this position in other geographic locations may differ. Certain positions may also be eligible for variable incentive compensation, such as bonuses or commissions, that is not included in the base pay.
If you have any questions or concerns about this posting, please email [email protected].
Requirements:
Why WWT?
At World Wide Technology, we work together to make a new world happen. Our important work benefits our clients and partners as much as it does our people and communities across the globe. WWT is dedicated to achieving its mission of creating a profitable growth company that is also a Great Place to Work for All. We achieve this through our world\-class culture, generous benefits and by delivering cutting\-edge technology solutions for our clients.
Founded in 1990, WWT is a global technology solutions provider leading the AI and Digital Revolution. WWT combines the power of strategy, execution and partnership to accelerate digital transformational outcomes for organizations around the globe. Through its Advanced Technology Center, a collaborative ecosystem of the world's most advanced hardware and software solutions, WWT helps clients and partners conceptualize, test and validate innovative technology solutions for the best business outcomes and then deploys them at scale through its global warehousing, distribution and integration capabilities.
With over 12,000 employees across WWT and Softchoice and more than 60 locations around the world, WWT's culture, built on a set of core values and established leadership philosophies, has been recognized 14 years in a row by Fortune and Great Place to Work® for its unique blend of determination, innovation and creating a great place to work for all.
Want to work with highly motivated individuals on high\-performance teams? Join WWT today!
AI Product Manager
The AI Product Manager is a strategic leader responsible for driving enterprise\-wide adoption of AI technologies, enabling organizational productivity, and delivering measurable business impact through AI\-driven solutions. This role integrates people, process, and technology to identify high value use cases, prioritize automation and AI opportunities, and deliver scalable AI products that support PMO, Engineering, and broader business transformation initiatives.
This role is central to shaping how the organization leverages Microsoft Copilot, automation platforms, workflow agents, and AI\-assisted productivity tools to modernize operations, accelerate delivery, and empower teams. The Product Manager partners with senior stakeholders, business units, IT, and cross\-functional teams to define and execute an AI roadmap aligned to corporate strategy.
The ideal candidate possesses a strong foundation in product management, a deep passion for AI\-led transformation, and hands\-on experience delivering intelligent solutions that improve efficiency, reduce manual effort, and elevate the employee experience.
This role emphasizes AI strategy, product leadership, stakeholder engagement, governance, and measurable value realization — driving a culture of innovation, experimentation, and continuous learning across the enterprise.
Job Responsibilities
- Own the AI product vision, roadmap, and execution strategy for enterprise\-wide AI enablement.
- Translate business needs into AI use cases, workflows, agents, and automation opportunities.
- Ensure AI solutions drive value across PMO, Engineering, Operations, and business stakeholders.
- Evaluate and operationalize new AI capabilities (e.g., Copilot agent mode, workflow agents, data integrations).
- Lead the creation of an AI Innovation Workbook, AI catalogs, and recurring AI health/status reviews.
- Champion adoption of Copilot, workflow automation, intelligent document processing, and data\-driven tools.
- Experiment with emerging AI capabilities; run proofs\-of\-concept; scale successful solutions.
- Evangelize best practices for prompt engineering, agent design, automation patterns, and AI governance.
- Lead and mentor a team of analysts, product owners, and AI enablers working across PMO and engineering.
- Foster a culture of curiosity, innovation, experimentation, and continuous improvement.
- Set clear expectations, provide coaching, and support team career development.
- Partner with business leaders to identify opportunities for AI\-driven transformation.
- Act as the primary liaison between Engineering, PMO, IT, Data Platforms, and business partners.
- Gather, validate, and prioritize AI implementation requests from multiple stakeholder groups.
- Conduct user interviews, process mapping sessions, and AI maturity assessments.
- Prioritize use cases based on complexity, ROI, value creation, and business urgency.
- Define user personas, journeys, and success criteria for AI experiences.
- Lead the delivery of workflow agents, copilots, dashboards, automations, and AI workflows.
- Coordinate cross\-functional teams including engineering, data, operations, and business analysts.
Ensure AI solutions go from concept MVP* enterprise scale successfully.
- Monitor AI solution performance, reliability, and adoption.
- Support incident response, risk mitigation, and change management.
- Ensure AI applications operate within required availability, security, and performance standards.
- Drive alignment between PMO leadership, engineering leaders, and enterprise stakeholders.
- Build AI adoption playbooks, training materials, release notes, and executive\-status updates.
- Facilitate “AI Weekly Status” meetings and reporting.
- Identify opportunities for automation and process enhancement across PMO and engineering.
- Champion a data\-driven culture using metrics, analytics, and AI usage insights.
- Introduce new efficiencies and reduce organizational manual effort by scaling AI capabilities.
- Track AI performance KPIs including time savings, productivity uplift, adoption, and cost avoidance.
- Build executive dashboards highlighting AI impact by function, workflow, and business value.
- Ensure each AI solution delivers measurable, repeatable returns.
- Ensure responsible AI usage aligned to enterprise standards, data privacy controls, and cybersecurity.
- Maintain documentation, models, and workflows within approved governance frameworks.
- Establish and enforce AI deployment standards and best practices.
Salary Context
This $130K-$163K range is in the lower quartile 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 World Wide Technology, 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 Required
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 ($147K) sits 31% below the category median. Disclosed range: $130K to $163K.
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.
World Wide Technology AI Hiring
World Wide Technology has 6 open AI roles right now. They're hiring across AI Software Engineer, AI Product Manager, AI/ML Engineer. Positions span Remote, US, St. Louis, MO, US, Seattle, WA, US. Compensation range: $150K - $235K.
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
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.