Principal AI Product & Strategy Manager, Technical

📍 Job Overview

Job Title: Principal AI Product & Strategy Manager, Technical

Company: T-Mobile

Location: Bellevue, Washington, United States / Frisco, Texas, United States

Job Type: Full time

Category: Product Management / AI & Machine Learning Strategy

Date Posted: 2026-08-12

Experience Level: 10+ years

Remote Status: Hybrid (3 days in office)

🚀 Role Summary

• Drives end-to-end product vision, strategy, and roadmap for flagship AI initiatives from concept to commercial launch within T-Mobile's AI Commercialization team.

• Combines customer understanding, strategic thinking, and hands-on execution to deliver AI products that create new revenue streams and differentiated customer experiences.

• Leads cross-functional teams, including engineering, project management, and marketing, to validate, build, and launch AI-powered solutions.

• Requires a unique blend of startup agility and enterprise scale capabilities to push the boundaries of AI in telecommunications.

📝 Enhancement Note: This role is positioned as a Principal-level Product Manager, indicating a high degree of autonomy, strategic influence, and leadership. The emphasis on "Technical" in the title and the requirement for hands-on coding/architecture experience suggests a deep understanding of the underlying technology is crucial, not just product strategy. The AI focus points towards specialization in Machine Learning, LLMs, and conversational AI.

📈 Primary Responsibilities

• Owns the product vision, strategy, and roadmap for flagship AI initiatives, from ideation through market launch.

• Conducts deep customer research and market analysis to identify breakthrough AI opportunities and develop compelling business cases.

• Defines success metrics, tracks progress against ambitious growth targets, and anticipates AI trends and competitive threats.

• Writes detailed product requirements, user stories, and acceptance criteria for AI-powered features, translating strategy into actionable development tasks.

• Collaborates with Technical Architects, UX/UI designers, and engineering teams to ensure technical feasibility, scalability, and timely delivery of AI solutions.

• Drives resolution of technical and business challenges, and coordinates with GTM and commercialization teams for successful launch strategies.

• Manages product quality and performance in the production environment, including accountability for defect response and stakeholder communication.

• Develops and maintains dashboards and reports tracking product health, success metrics, and technical KPIs.

• Leads customer discovery, validation, and user testing, advocating for customer needs and ensuring exceptional user experience.

• Represents T-Mobile at industry events and innovation forums, sharing best practices and fostering relationships with external partners.

📝 Enhancement Note: The responsibilities highlight a strong focus on both strategic product definition and hands-on technical execution. The requirement to "write production code, solution engineering, or technical architecture" in a previous role is a key differentiator for this "technical" product management position.

🎓 Skills & Qualifications

Education:

• Bachelor's Degree in Computer Science, Engineering, IT, or equivalent practical experience. Experience:

• 8+ years of hands-on technical experience in a role involving writing production code, solution engineering, or technical architecture within a large-scale company or application environment.

• More than 10 years of relevant Product Management experience in an agile software product development environment. Required Skills:

• Business Operations Mastery: Demonstrates complete mastery of business-side skills (communication, customer research, product vision, feature definition) alongside technical architecture, development, and execution skills.

• Business Analysis: Validated analytical skills with the ability to identify, analyze, and synthesize product usage data to drive decisions.

• Customer Experience Management: Industry-leading understanding of customer experience principles and their application to AI products.

• Technology Expertise: Mastery-level understanding of platform technologies and components (security, performance, optimization, API integration) and expert knowledge of the full technology stack for assigned products.

• Agile Methodologies: Proven success in directing matrixed resources and delivering software using Agile Scrum methodologies across multiple teams.

• Innovation Methodology: Expertise in design thinking, lean startup methodologies, rapid prototyping, and hypothesis-driven development.

• Communication: Ability to effectively communicate with leadership, technical, and non-technical audiences with a high degree of collaboration and influence.

• AI/ML Product Expertise: Deep understanding of AI technologies, capabilities, and limitations, with experience in LLMs, conversational AI, and ML platforms.

• Data-Driven Decision Making: Proficiency with analytics tools and metrics-based product optimization.

Preferred Skills:

• Partnership Development: Experience working with external partners, vendors, and ecosystem players.

• Collaboration: Experience with successive elaboration and developing Initiatives, Features, and User Stories for DevOps teams.

• Integration: Knowledge and experience with integration patterns, APIs, and protocols such as REST, EDI, SOAP, etc.

• Product Management: Experience delivering large and complex business/technology initiatives as a Product Manager or in a lead technology role.

📝 Enhancement Note: The combination of deep technical background (8+ years in coding/architecture) with extensive product management experience (10+ years in Agile) is a critical requirement. The emphasis on "mastery" in several areas indicates a senior-level expectation.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Showcase of AI product initiatives managed from concept to launch, demonstrating strategic thinking and execution.

• Examples of detailed product requirements, user stories, and acceptance criteria for complex AI features.

• Documentation of customer research, market analysis, and business case development for AI products.

• Evidence of successful collaboration with engineering, design, and GTM teams on AI product delivery.

• Metrics and KPIs demonstrating the impact and success of launched AI products, including ROI analysis. Process Documentation:

• Workflow examples illustrating how market analysis and customer insights were translated into product roadmaps and feature definitions.

• Demonstrations of hypothesis-driven testing, rapid prototyping, and MVP development cycles used in AI product development.

• Documentation of how technical challenges were identified, communicated, and resolved in collaboration with engineering teams.

• Examples of cross-functional team alignment and dependency management for complex AI initiatives.

• Case studies detailing the process of defining, tracking, and reporting on product health and success metrics for AI solutions.

📝 Enhancement Note: While not explicitly stated, a portfolio demonstrating successful AI product launches, technical understanding, and strategic product management is implicitly required for a Principal-level role. Candidates should be prepared to detail their process for product discovery, development, launch, and iteration, particularly for AI/ML products.

💵 Compensation & Benefits

Salary Range: $139,700 - $252,000 USD per year

Base Pay Range Explanation: The provided salary range is for a successful candidate in the role. Actual pay will vary based on factors such as work location, qualifications, and experience. T-Mobile also offers a lookup tool for location-specific pay ranges.

Bonus Target:

• Corporate Bonus Target: 20% of base salary.

• Eligibility for annual bonus based on company and/or individual performance. Benefits:

• Medical, Dental, and Vision Insurance

• Flexible Spending Account

• 401(k) plan

• Employee Stock Grants

• Employee Stock Purchase Plan

• Paid Time Off (PTO)

• Up to 12 Paid Holidays (approx. 4 weeks for new full-time employees)

• Paid Parental and Family Leave

• Family Building Benefits

• Back-up Care

• Enhanced Family Support

• Childcare Subsidy

• Tuition Assistance

• College Coaching

• Short-term and Long-term Disability Insurance

• Voluntary AD&D Coverage

• Voluntary Accident Coverage

• Voluntary Life Insurance

• Voluntary Disability Insurance

• Voluntary Long-term Care Insurance

• Mobile Service & Home Internet Discounts

• Pet Insurance

• Commuter and Transit Programs Working Hours:

• Standard full-time hours, likely 40 hours per week, with flexibility expected for a Principal-level role in a fast-paced environment.

📝 Enhancement Note: The salary range is competitive for a Principal-level technical product management role, especially in the technology sector. The comprehensive benefits package reflects T-Mobile's commitment to employee well-being and financial security. The bonus target is significant and aligns with the role's impact.

🎯 Team & Company Context

🏢 Company Culture

Industry: Telecommunications

Company Size: T-Mobile is a large, publicly traded company with tens of thousands of employees globally. This scale offers resources and impact but also requires navigating larger organizational structures.

Founded: T-Mobile USA was founded in 1994, evolving significantly through mergers and acquisitions, including its major merger with Sprint in 2020, making it a dominant player in the US market.

Team Structure:

• This role sits within T-Mobile's AI Commercialization team, suggesting a focus on bringing AI innovations to market.

• It will involve close collaboration with cross-functional teams, including Product, IT, Data & AI organizations, Engineering, UX/UI Design, Project/Program Management, Marketing, Sales, Legal, and Finance.

• The "Principal" title implies potential for mentoring junior team members and influencing broader product strategy across multiple teams. Methodology:

• Operates in a hybrid work environment, requiring 3 days per week in the office, fostering a blend of in-person collaboration and remote flexibility.

• Employs Agile methodologies for software development, with a focus on efficiency, lean practices, elimination of waste, and DevOps/CI/CD principles.

• Utilizes hypothesis-driven testing, rapid prototyping, and MVP development cycles to validate and iterate on AI product concepts.

• Data-driven decision-making is core, with emphasis on analyzing quantitative and qualitative data to identify opportunities and measure product success.

Company Website: https://www.t-mobile.com/

📝 Enhancement Note: T-Mobile is known for its "Un-carrier" culture, emphasizing innovation, customer focus, and a less traditional corporate structure. The AI Commercialization team likely operates with a startup-like agility within this larger enterprise framework.

📈 Career & Growth Analysis

Operations Career Level: Principal Product & Strategy Manager, Technical. This is a senior individual contributor role with significant strategic responsibility and the potential for leadership influence. It signifies expertise and a high level of impact.

Reporting Structure: While not explicitly stated, a Principal Product Manager typically reports to a Director or VP of Product Management or a related AI/Technology leadership role. They will manage a portfolio of complex initiatives and may indirectly lead cross-functional teams.

Operations Impact: This role has the potential for substantial impact by driving the development and commercialization of AI products that can create new revenue streams, enhance customer experiences, and differentiate T-Mobile in the competitive telecommunications market. Success will be measured by product adoption, revenue generation, and strategic market positioning.

Growth Opportunities:

• Leadership Advancement: Potential to move into Director-level product roles, manage larger product portfolios, or lead broader AI strategy initiatives.

• Specialization Deepening: Opportunity to become a recognized expert in specific AI domains (e.g., LLMs, conversational AI) within the telecommunications industry.

• Cross-Functional Exposure: Gaining deep insights into various business units (Sales, Marketing, Operations, Engineering) to broaden understanding of enterprise-wide challenges and opportunities.

• Mentorship & Influence: Opportunity to mentor junior product managers and influence product strategy across the organization.

• Industry Recognition: Potential to represent T-Mobile at industry events, contributing to thought leadership in AI product management.

📝 Enhancement Note: The "Principal" title suggests this is a key role for T-Mobile's AI strategy, offering significant growth potential for individuals who can demonstrate strategic vision, technical acumen, and successful product execution.

🌐 Work Environment

Office Type: Hybrid work environment requiring 3 days per week in the office. This suggests a modern office setup designed for collaboration, with access to necessary technology and resources.

Office Location(s):

• Bellevue, Washington (likely near T-Mobile's Washington HQ)

• Frisco, Texas (near T-Mobile's Texas operations hub)

Candidates must be located in or willing to relocate to one of these areas.

Workspace Context:

• The environment is described as "fast-paced" and "entrepreneurial," indicating a dynamic and potentially demanding workplace.

• Expect a collaborative setting where cross-functional teams work closely together to achieve ambitious goals.

• Access to T-Mobile's standard technology infrastructure, tools, and development environments will be provided.

• Opportunities for interaction with diverse teams are inherent to the role's collaborative nature. Work Schedule:

• Full-time employment. While standard business hours are expected, the nature of product management, especially in AI, often requires flexibility to meet deadlines and address critical issues, particularly during launch phases or when dealing with production incidents.

📝 Enhancement Note: The hybrid model is a key aspect of the work environment, emphasizing the need for strong remote communication skills alongside in-person collaboration. Being based in either Bellevue or Frisco means candidates should be aware of the tech industry landscape and cost of living in those regions.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: HR or recruiter screen to assess basic qualifications and cultural fit.

• Hiring Manager Interview: Deeper dive into experience, technical background, and strategic thinking related to AI product management.

• Technical Deep Dive: Potential interviews with engineering leads, architects, or data scientists to assess technical depth and problem-solving abilities.

• Cross-Functional Interviews: Discussions with stakeholders from marketing, GTM, or other business units to evaluate collaboration and communication skills.

• Product Strategy/Case Study: A simulated product challenge or presentation of a past project to assess strategic approach, analytical skills, and ability to articulate vision and execution plans.

• Executive/VP Level Interview: Final discussion with senior leadership to assess strategic alignment, leadership potential, and overall fit for the Principal role.

Portfolio Review Tips:

• Quantify Impact: For each project, clearly articulate the problem, your role, the solution, and the measurable outcomes (e.g., revenue generated, cost savings, customer satisfaction improvements, adoption rates). Use specific numbers and KPIs.

• Showcase Technical Depth: For AI products, be prepared to discuss the underlying technologies, architectural considerations, data challenges, and how you navigated them. Highlight your hands-on technical background.

• Demonstrate Strategic Thinking: Explain your product vision, how you developed the roadmap, and how your decisions aligned with T-Mobile's business objectives.

• Highlight Collaboration: Provide examples of how you worked effectively with diverse teams (engineering, design, marketing, etc.) to bring products to market.

• Structure for Clarity: Organize your portfolio logically, perhaps by product lifecycle phase or by key AI capabilities. Use clear, concise language, and visual aids where appropriate.

• Tailor to AI: Emphasize your experience with AI/ML concepts, LLMs, conversational AI, and the unique challenges of developing and launching AI products.

Challenge Preparation:

• Understand T-Mobile's Business: Research T-Mobile's current market position, strategic priorities, and recent AI initiatives.

• AI Product Ideation: Be ready to brainstorm new AI product ideas relevant to the telecommunications industry, considering customer needs and business value.

• Problem-Solving Scenarios: Prepare for hypothetical scenarios involving technical challenges, market shifts, or prioritization conflicts related to AI product development.

• Communication Practice: Rehearse explaining complex technical concepts and product strategies clearly and persuasively to both technical and non-technical audiences.

📝 Enhancement Note: Given the "Principal" title and technical focus, candidates should prepare to deeply discuss their past technical contributions and strategic product decisions, especially those involving AI/ML. Portfolio examples should heavily feature quantifiable results and evidence of technical leadership.

🛠 Tools & Technology Stack

Primary Tools:

• CRM: Salesforce (likely used for customer data and sales/service insights, though not explicitly mentioned for this role, it's a common enterprise tool).

• Project Management: Jira, Confluence (standard for Agile development, user story creation, documentation, and workflow tracking).

• Collaboration Tools: Microsoft Teams, Slack (essential for hybrid work and cross-functional communication).

• Product Management Platforms: Tools for roadmap planning, feature prioritization, and backlog management (e.g., Aha!, Productboard, or internal T-Mobile solutions).

Analytics & Reporting:

• Data Visualization: Tableau, Power BI (for creating dashboards and reports on product performance, user behavior, and technical KPIs).

• Analytics Platforms: Google Analytics, Adobe Analytics, or internal data platforms for tracking user engagement and product usage.

• Data Science Tools: Python (with libraries like Pandas, NumPy, Scikit-learn), R (for data analysis, model building, and working with data scientists).

CRM & Automation:

• AI/ML Platforms: Experience with cloud-based ML platforms (e.g., AWS SageMaker, Google AI Platform, Azure Machine Learning) and specific AI technologies like LLMs, conversational AI frameworks.

• API Integration Tools: Understanding of REST, SOAP, EDI protocols and tools for API management and testing.

• DevOps/CI/CD Tools: Jenkins, GitLab CI, Docker, Kubernetes (for understanding the deployment and operational aspects of AI products).

📝 Enhancement Note: While the job description doesn't list specific tools, the requirements for technical architecture, agile development, data analysis, and AI/ML indicate proficiency with a broad range of modern software development and data science tools. Experience with cloud platforms (AWS, Azure, GCP) is highly probable.

👥 Team Culture & Values

Operations Values:

• Customer First: A core T-Mobile value, emphasizing a relentless focus on understanding and meeting customer needs, especially critical for AI products aiming to improve user experience and create value.

• Innovation & Agility: Encouraging new ideas, rapid experimentation, and the ability to adapt quickly to market changes and technological advancements, aligning with the "startup agility" mentioned.

• Accountability & Ownership: Taking responsibility for product success from concept to delivery, including technical performance and market impact, especially important for a Principal role.

• Collaboration & Teamwork: Working effectively across diverse teams to achieve shared goals, fostering a "One Team, Together" spirit.

• Data-Driven Decision Making: Using data and analytics to inform product strategy, prioritize features, and measure success.

Collaboration Style:

• Highly collaborative, with an expectation of working closely with engineering, design, marketing, and other business units.

• Success relies on strong communication, negotiation, and influencing skills to align stakeholders and drive consensus.

• The hybrid model necessitates effective virtual collaboration tools and techniques alongside in-person interactions.

• A culture of constructive feedback and continuous improvement is likely, especially within the Agile framework.

📝 Enhancement Note: T-Mobile's "Un-carrier" culture is deeply ingrained, emphasizing disruption, customer advocacy, and a dynamic, forward-thinking approach. Candidates should align with these values.

⚡ Challenges & Growth Opportunities

Challenges:

• Balancing Innovation and Scale: Integrating cutting-edge AI technologies into a large enterprise environment while ensuring scalability, reliability, and compliance.

• Cross-Functional Alignment: Navigating complex organizational structures and securing buy-in from various departments with potentially competing priorities.

• Rapid AI Evolution: Keeping pace with the extremely fast-moving field of AI/ML, ensuring product strategies remain relevant and competitive.

• Technical Debt Management: Balancing the need for rapid feature delivery with the long-term technical health and maintainability of AI platforms.

• Data Privacy & Ethics: Ensuring AI products are developed and deployed responsibly, adhering to data privacy regulations and ethical considerations.

Learning & Development Opportunities:

• AI/ML Specialization: Deepening expertise in cutting-edge AI technologies, potentially through internal training, external conferences, or specialized projects.

• Product Leadership: Developing strategic leadership skills, influencing senior stakeholders, and potentially managing larger product portfolios.

• Industry Exposure: Gaining deep insights into the telecommunications industry and its intersection with AI, potentially representing T-Mobile externally.

• Technical Breadth: Expanding knowledge across the full technology stack and understanding complex system integrations.

• Mentorship: Learning from and mentoring other product managers, contributing to the growth of the product organization.

📝 Enhancement Note: This role offers a significant opportunity to shape the future of AI at a major telecommunications company, facing complex challenges that drive professional growth and skill development.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you developed a product strategy for a complex AI/ML initiative. What was your process, and what were the key outcomes?" (Focus on vision, roadmap, customer research, and metrics.)

• "How would you prioritize features for an AI product with limited engineering resources, considering both technical feasibility and business impact?" (Prepare to discuss prioritization frameworks and trade-off decisions.)

• "Imagine T-Mobile wants to leverage LLMs to improve customer service. Outline a product strategy, including key features, target users, and success metrics." (Demonstrate your understanding of LLMs and their application in telecom.)

• "How do you balance the need for rapid innovation with the requirements for technical architecture, scalability, and long-term maintainability in AI products?" (Showcase your technical background and strategic planning.) Company & Culture Questions:

• "What excites you about T-Mobile's 'Un-carrier' approach, and how would you apply that mindset to AI product development?" (Research T-Mobile's values and culture.)

• "Describe your experience working in a hybrid environment and collaborating with distributed teams. How do you ensure effective communication and alignment?" (Highlight your adaptability and collaboration skills.)

• "How do you stay current with the rapidly evolving AI landscape, and how do you incorporate new trends into product strategy?" (Showcase your continuous learning mindset.) Portfolio Presentation Strategy:

• Start with the "Why": Clearly articulate the business problem or customer need your product addressed.

• Detail Your Role & Process: Explain your specific contributions, your product management process, and your technical background. Use the STAR method (Situation, Task, Action, Result).

• Quantify Everything: Present concrete metrics demonstrating ROI, adoption, efficiency gains, or customer satisfaction improvements.

• Highlight AI/Technical Nuances: For AI projects, discuss the technical architecture, data challenges, model selection rationale, and any unique development hurdles you overcame.

• Showcase Collaboration: Illustrate how you partnered with engineering, design, marketing, and other stakeholders to achieve success.

• Conclude with Future Vision: Briefly touch on what you learned and how it might inform future product development.

📝 Enhancement Note: Candidates should be prepared to go deep on both the strategic "what and why" and the technical "how" for their past AI product successes. Quantifiable results and a clear demonstration of leadership and technical acumen are paramount.

📌 Application Steps

To apply for this Principal AI Product & Strategy Manager position:

• Submit your application through the T-Mobile Workday careers portal using the provided URL.

• Portfolio Customization: Prepare a portfolio that highlights 2-3 key AI product initiatives. Focus on projects where you demonstrated both strategic product leadership and a strong technical understanding. Quantify the business impact and ROI for each.

• Resume Optimization: Tailor your resume to explicitly showcase your 10+ years of product management experience in Agile environments and your 8+ years of hands-on technical experience (coding, architecture, solution engineering). Use keywords from the job description, such as "AI," "LLMs," "Product Strategy," "Technical Architecture," and "Agile."

• Interview Preparation: Practice articulating your product vision, technical approach, and collaboration strategies. Be ready to discuss your portfolio projects in detail, using the STAR method and emphasizing quantifiable results.

• Company Research: Familiarize yourself with T-Mobile's current business objectives, its "Un-carrier" culture, and any recent AI or technology announcements. Understand their market position and competitive landscape.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.