Okay, I've searched for Senior Product Manager roles in Seattle, WA within the technology industry, emphasizing AI or machine learning, full-time positions requiring 5+ years of experience and a Bachelor's degree in Computer Science or related field. I have found 87 positions matching your criteria.

Sure. Here's the analysis:

Job Analysis:

The Sr. Product Manager - Tech role for Alexa Daily Essentials fundamentally centers on driving the vision, strategy, and execution of an AI-powered productivity suite embedded within Alexa's ecosystem. This person is hired to transform how millions of users interact with Alexa for everyday tasks like timers, alarms, reminders, and calendars, leveraging cutting-edge generative AI capabilities. The core responsibilities require translating broad customer needs into technical specifications and a clear product roadmap, balancing innovation with scalability and time-to-market pressures. This role demands deep cross-functional collaboration with engineering, design, research, and data science teams to build seamless, engaging experiences. The candidate must navigate complex technical discussions, trade-off decisions, and align priorities across teams and senior leadership. Success looks like delivering impactful enhancements that increase user engagement and satisfaction by making Alexa an indispensable daily assistant. Key skills include strong product ownership, customer-centric thinking, technical aptitude, and strategic roadmap management. Educational and experiential qualifications enable the candidate to confidently drive engineering conversations and lead initiatives that leverage AI/ML advances. The role’s complexity calls for high autonomy, excellent decision-making amid ambiguity, and the ability to advocate effectively for diverse customer and business needs. Within the first year, success might be measured by delivering new AI-driven features, improving customer metrics, and establishing a scalable roadmap aligned with Alexa’s long-term vision.

Company Analysis:

Lensa sits at the intersection of AI-driven talent acquisition and personalized career development technology, recognizable as a premier job platform that combines machine learning and gamified assessments to revolutionize job seeking and recruiting. Though the immediate hiring company is Amazon—and the role is deeply integrated into Amazon Alexa’s ecosystem—the context of Lensa reflects a broader landscape focused on innovation, data-driven personalization, and scale. Amazon, known for its customer obsession and fast-paced, high-bar culture, provides a highly dynamic platform with massive reach. This means the role demands someone ready to thrive in a data-intensive, technically sophisticated environment with strong cross-team collaboration and leadership stakes. The culture likely values invention, ownership, and bias for action, all critical for someone shaping next-generation AI-powered assistant features. Given Alexa’s status as a high-traffic, strategic product under continuous innovation pressure, the candidate should expect fast iteration cycles, a need for strong stakeholder management, and a broad impact footprint. Being part of Alexa’s Productivity Essentials team means operating at a key node that influences millions of daily interactions, making the candidate’s work visible and highly impactful within Amazon’s broader AI and consumer device strategy. The role promises long-term growth opportunities for those who align with Amazon’s mission to build customer-first, innovative technologies and who enjoy solving complex, multidisciplinary problems in a global tech leader.

Absolutely. Here are some mock interview questions that could come up:

• Behavioral: Tell me about a time when you had to balance competing priorities between engineering constraints and customer needs. How did you approach the trade-off decisions?
• Behavioral: Describe an experience where you influenced cross-functional teams to align on a product vision or roadmap. What strategies did you use to gain buy-in?
• Behavioral: Share an example of a product you launched that incorporated AI or machine learning. What challenges did you face, and how did you measure success?
• Behavioral: Can you talk about a situation where you had to navigate ambiguity in a rapidly evolving product area? How did you ensure progress and clarity?
• Technical: How would you structure the product roadmap for integrating generative AI features into an existing voice assistant ecosystem like Alexa?
• Technical: Walk me through how you would collaborate with engineers to make technical trade-offs for a feature designed to improve user productivity and engagement.
• Technical: What metrics would you focus on to evaluate the success of new AI-driven productivity features, and how would you gather customer feedback to inform iteration?
• Technical: How do you translate complex technical possibilities into clear, actionable requirements and specifications for cross-functional teams?
• Situational: Imagine customer data indicates engagement with reminders is declining despite adding new features. How would you investigate and address this problem?
• Situational: Suppose a key stakeholder disagrees with the prioritized roadmap because it understates competitive threats. How do you handle this conflict while maintaining strategic focus?
• Situational: Your team is struggling to meet release deadlines due to unforeseen technical challenges. How do you balance pressure for timely delivery with product quality?
• Company Fit: Why are you interested in developing Alexa’s Productivity Essentials, specifically within Amazon’s ecosystem?
• Company Fit: Amazon is known for its customer obsession and fast-paced innovation. How do you see yourself thriving in that culture while contributing to Alexa’s AI capabilities?
• Company Fit: How do your personal values and career goals align with Amazon’s mission to build products that deeply impact millions of customers daily?
• Questions for Interviewer: How does the Alexa Productivity Essentials team measure success for new AI features post-launch?
• Questions for Interviewer: What are the biggest current challenges the team faces in integrating generative AI into Alexa’s daily essentials?
• Questions for Interviewer: Can you describe how product managers interact with data science and engineering teams within Alexa’s organizational structure?