Product Manager II, Generative AI, Google Cloud

As a Product Manager II, Generative AI at Google Cloud, your primary responsibilities will include steering product development from conception to launch, defining product roadmaps aligned with strategic initiatives, and driving interaction with partner teams such as engineering and UX to ensure requirements are met. You will also validate market opportunities and oversee product life cycles from launch to retirement.

To qualify for the Product Manager II, Generative AI role at Google Cloud, you need a Bachelor’s degree or equivalent practical experience along with 5 years of experience in product management or related technical roles. Knowledge and experience in Generative AI or Large Language Models are essential, and preferred qualifications include a Master’s degree and additional experience in strategic marketing or technical leadership.

A typical day for a Product Manager II, Generative AI at Google Cloud entails cross-collaboration with various teams to implement product requirements, engaging in strategic planning sessions, analyzing market trends, and iterating on feedback to enhance product performance. You’ll also manage project timelines and coordinate with stakeholders to keep them aligned with the product vision.

At Google Cloud, ongoing learning and development are embedded in the culture. As a Product Manager II, you’ll have access to workshops, mentoring programs, and cutting-edge resources to deepen your knowledge in AI and product management. Google emphasizes personal growth, empowering you to stay on top of industry trends and enhance your professional skill sets.

The US base salary range for the Product Manager II, Generative AI role at Google Cloud is approximately $156,000 to $229,000. This range reflects the position's complexities and location, with individuals potentially earning bonuses, equity, and benefits in addition to their base salary.

Highlight your technical background and specific instances where you've worked on projects involving Generative AI. Discuss how you facilitated collaboration among technical teams to drive product outcomes, demonstrating your ability to merge business strategies with innovative technology.

When prioritizing features, I assess factors such as user needs, market demand, and alignment with business goals. I use frameworks like MoSCoW (Must have, Should have, Could have, and Won't have) to categorize and communicate priorities effectively across teams.

Building strong relationships is vital. I present clear metrics and data-driven insights that align product vision with stakeholder interests while fostering open communication and involving them in the decision-making process to secure their support.

I managed a product that faced integration challenges with existing systems. By collaborating with engineering teams and iterating on user feedback, we redefined our approach, ultimately enhancing product usability and satisfaction.

Post-launch, I track key performance indicators (KPIs) relevant to user engagement, satisfaction, and business impact. Regular assessments and feedback loops are essential to ensure the product aligns with strategic goals and user needs.

In one instance, a product launch did not meet initial expectations. I organized a retrospective meeting with stakeholders, analyzed the reasons, and used feedback to refine our strategies, demonstrating that learning from failures can drive future success.

I prefer using Agile methodologies and tools like JIRA and Trello for project tracking. These enable responsive adjustments based on team input and market changes while keeping tasks organized and communication streamlined.

Balancing technical constraints with business needs involves clear communication with engineering teams to understand limitations while advocating for user requirements. Finding creative solutions that satisfy both ends is key to successful product outcomes.

Customer feedback is invaluable. I incorporate user feedback during the development process to identify pain points and adjust our offerings accordingly, ensuring we design products that genuinely solve user problems.

I actively engage with industry literature, participate in webinars, and network with professionals in tech meetups to stay informed on AI trends. Continuous learning is crucial in such a rapidly evolving field.