Lead Product Manager - Digital Acquisitions

Lead Product Manager - Digital Acquisitions

Location: Plano,TX

Note:Inperson Interview

About the Job

We're looking for an experienced Lead Product Manager to lead product strategy and discovery for our next-generation digital customer experiences. This isn't a role where you'll manage a backlog of stakeholder requests. This is a role where you'll own outcomes, lead continuous discovery, and build products that customers love while driving measurable business impact.

As a Lead PM, you'll work at the intersection of customer needs, business strategy, and emerging technology—particularly AI/ML—to discover and deliver solutions that transform how millions of customers experience connectivity, personalization, and digital services. You'll operate as part of an empowered product trio (PM, Designer, Engineer) with the autonomy to discover the right solutions and the accountability to deliver meaningful outcomes.

You'll be joining a digital product organization that's committed to modern product practices: we practice continuous discovery with weekly customer touchpoints, we use opportunity solution trees to visualize our thinking, we run assumption tests before building, and we measure success by outcomes, not output.

Strategic Context:

AT&T is investing heavily in digital transformation, 5G infrastructure, fiber expansion to 50M+ locations, and AI-powered personalization. We're focused on creating customer-centric products and services that leverage our network leadership to deliver greater value, personalization, and security. As a Lead PM, you'll play a critical role in defining how we use AI and advanced technologies to create experiences that differentiate us in the market and drive sustainable growth.

This role reports to the Director of Digital Product and will influence product strategy across multiple teams and business units.

What You'll Do

Product Strategy & Outcomes
 

• Own and drive product strategy for [specific product area], defining clear outcome-based objectives that align with business goals
• Translate business strategy into product strategy, identifying the critical problems we need to solve to achieve our desired outcomes
• Set and manage team OKRs that empower your product trio to discover solutions rather than build prescribed features
• Develop product vision and roadmap that balances short-term impact with long-term strategic positioning
• Identify opportunities where AI/ML can create differentiated customer value and build business leverage

Continuous Discovery
 

• Lead weekly customer interviews and research activities with your product trio to maintain continuous customer contact
• Map and prioritize opportunities using opportunity solution trees, ensuring your team is always working on the highest-impact problems
• Design and run assumption tests and experiments to validate solutions before committing to full development
• Synthesize customer insights, market trends, and data analytics to inform product decisions
• Build rapid prototypes and MVPs to test hypotheses with real customers and iterate based on learning

AI/ML Product Development
 

• Identify and prioritize opportunities where generative AI, machine learning, and advanced analytics can solve customer problems or create business value
• Partner with data science and ML engineering teams to scope, design, and ship AI-powered features and experiences
• Define success metrics and measurement frameworks for AI/ML initiatives, including model performance, customer satisfaction, and business impact
• Navigate the unique challenges of AI product development: managing uncertainty, setting appropriate quality bars, handling edge cases, and building responsible AI practices
• Stay current on AI/ML capabilities and trends, translating technical possibilities into customer-valuable product opportunities

Cross-Functional Leadership
 

• Build and maintain strong collaborative relationships with engineering, design, data science, marketing, operations, and business stakeholders
• Influence without authority across the organization, using data, customer insights, and strategic thinking to build alignment
• Coach and elevate product thinking across your immediate team and the broader organization
• Navigate organizational complexity to ship products, managing dependencies and aligning diverse stakeholders around shared outcomes
• Present product strategy, discovery learnings, and business results to senior leadership

Team Development & Culture
 

• Champion continuous discovery, experimentation, and customer-centricity across the organization
• Model the behaviors of an empowered product team: showing work, sharing learning, defaulting to action with appropriate risk management
• Contribute to building a product culture that values outcomes over outputs and learning over perfection

Experience & Qualifications

Required Experience

Product Management Excellence:
 

• 7+ years of product management experience building digital products, with at least 3 years in a senior or lead role
• Proven track record of shipping successful products that delivered measurable customer and business outcomes
• Experience owning product strategy end-to-end: from discovery through delivery to measuring impact
• Deep understanding of modern product practices including continuous discovery, assumption testing, and outcome-based roadmapping
• Portfolio of products where you can demonstrate the progression from customer problem to shipped solution to measured impact

AI/ML Product Experience:
 

• 1+ years of hands-on experience building and shipping AI/ML-powered products or features
• Direct experience working with data science and ML engineering teams to scope, develop, and deploy machine learning models in production
• Understanding of AI/ML product lifecycle: data requirements, model training and evaluation, deployment considerations, monitoring, and continuous improvement
• Experience with at least one of the following AI/ML applications: recommendation systems, personalization engines, natural language processing/LLMs, predictive analytics, computer vision, or conversational AI
• Demonstrated ability to translate technical AI/ML capabilities into valuable customer experiences
• Experience defining success metrics and quality standards for AI-powered features, including both model performance metrics and customer/business outcomes

Continuous Discovery Practices:
 

• Demonstrated experience conducting regular customer interviews and research as part of product development (not delegated to a research team)
• Experience using opportunity solution trees, customer journey maps, or similar frameworks to visualize discovery work
• Track record of running assumption tests, prototypes, and experiments to validate ideas before building
• Comfortable working in ambiguity and making decisions with incomplete information, then learning quickly through experimentation

Cross-Functional Leadership:
 

• Proven ability to influence and align diverse stakeholders including executives, engineering leaders, designers, and business partners
• Experience leading product trios or cross-functional teams where decision-making is collaborative, not hierarchical
• Strong communication skills: can articulate strategy, rally teams around outcomes, and present to senior leadership
• Experience managing complex products with multiple dependencies and stakeholders

Strongly Preferred Experience

Domain Expertise:

Experience in telecommunications, consumer digital services, B2C/B2B2C products, or enterprise SaaS
Background in products serving millions of users at scale
Experience with personalization, recommendation systems, or customer engagement platforms
Understanding of digital commerce, subscription models, or customer lifecycle management

Advanced AI/ML:
 

• Experience with generative AI products or integrating LLMs (GPT, Claude, Gemini etc.) into customer-facing applications
• Familiarity with responsible AI practices: bias detection, fairness, transparency, privacy, and ethical AI development
• Experience with AI-powered customer service, conversational interfaces, or intelligent automation
• Understanding of data pipelines, feature engineering, and the infrastructure needed to support ML at scale

Product Leadership:

Experience coaching or mentoring other product managers
Track record of improving product practices or culture within an organization
Experience leading transformation from feature teams to empowered product teams
Public speaking, writing, or thought leadership in product management
Technical Depth:

Background in software engineering or technical degree (Computer Science, Engineering, etc.)
Ability to read code and engage in technical discussions with engineering teams
Understanding of modern software architectures, APIs, cloud platforms, and data infrastructure
Experience with analytics tools, A/B testing platforms, and product instrumentation
Skills & Competencies

Core Product Skills

Strategic Thinking: Ability to connect customer problems to business strategy and translate strategy into actionable product direction
Customer Empathy: Deep curiosity about customers, their contexts, and their unmet needs; cognitive empathy to understand diverse user perspectives
Critical Thinking: Can analyze complex problems, identify root causes, and generate multiple solution hypotheses
Decision-Making: Comfortable making decisions with incomplete information while managing risk appropriately
Execution Excellence: Ability to move from insight to shipped product with speed and quality

AI/ML Product Competencies
 

• Technical Fluency: Can engage in detailed conversations about model design, performance, and trade-offs
• Problem Framing: Ability to identify problems well-suited for AI/ML solutions vs. those better solved with traditional approaches
• Experimentation Mindset: Comfortable with the iterative, probabilistic nature of ML development and can design appropriate testing frameworks
• Quality Standards: Can define what "good enough" means for AI features, balancing accuracy, latency, cost, and customer experience
• Responsible AI: Awareness of bias, fairness, privacy, and ethical considerations in AI product development

Discovery & Research Skills

Interview Technique: Skilled at conducting story-based customer interviews that reveal genuine needs and behaviors
Synthesis: Ability to find patterns across qualitative and quantitative data to identify high-impact opportunities
Assumption Testing: Can design and run rapid experiments to test critical assumptions before building
Visual Thinking: Comfortable using frameworks like opportunity solution trees, story maps, or journey maps to organize thinking
Collaboration & Influence

Stakeholder Management: Can build trust and alignment with diverse stakeholders through transparency and data-driven storytelling
Influential Communication: Persuasive written and verbal communication; can tailor message to technical and non-technical audiences
Coaching: Able to elevate the product thinking of teammates, engineers, and designers through questions and frameworks
Conflict Navigation: Skilled at finding win-win solutions when stakeholders have competing priorities
Personal Attributes

High Agency: Takes ownership, seeks solutions, and drives outcomes without waiting for permission
Intellectual Curiosity: Constantly learning about customers, technology, market, and craft
Resilience: Comfortable with setbacks, failed experiments, and course corrections
Humility: Willing to be wrong, learn from mistakes, and give credit generously
Adaptability: Thrives in fast-changing environments with evolving priorities
Education

Bachelor's degree in computer science, Engineering, Business, Design, or related field required
MBA or advanced technical degree (MS in CS, Data Science, HCI) preferred but not required
Continuous learning through books, courses, conferences more important than formal