Product Manager, AI Enrichment

As a Product Manager for AI Enrichment at Relativity, your responsibilities will include defining and executing product roadmaps, driving product discovery, measuring product success through key metrics and quarterly OKRs, and supporting development teams by translating validated designs into actionable story cards. You'll also partner closely with engineering to ensure the deliverables meet high standards for scalability, reliability, and security.

To excel as a Product Manager for AI Enrichment at Relativity, you'll need at least 3+ years of experience in software product management, along with strong expertise in design thinking and iterative software development processes. A background in AI-powered solutions and comfort with data analysis to monitor product health and success will also set you apart.

The expected salary range for the Product Manager for AI Enrichment role at Relativity falls between $115,000 to $173,000. Actual salaries may vary and will be influenced by your experience, skill set, qualifications, and internal pay equity, with a focus on allowing for meaningful salary growth in this position.

At Relativity, we are committed to your growth as a Product Manager for AI Enrichment. Our culture encourages continuous learning, knowledge sharing with cross-functional teams, and opportunities to lead innovative AI-powered product initiatives. We aim to develop skills that aid in career advancement while fostering a supportive environment.

In addition to a competitive salary, Relativity offers a robust benefits package for Product Managers for AI Enrichment, including flexible work arrangements, a winter break from Christmas to New Year's Day, 401k matching, and paid parental leave. We want to ensure our employees feel valued and supported both personally and professionally.

When prioritizing features for AI Enrichment products, I assess customer feedback, product metrics, and alignment with strategic goals. Using frameworks like the RICE method (Reach, Impact, Confidence, and Effort) helps in making informed decisions about what will provide the most value to our users at Relativity.

In my previous roles, I have successfully managed AI-powered products, overseeing their full lifecycle from ideation to launch. My experience includes collaborating with data scientists to develop algorithms and ensuring the solutions adhere to AI ethics, making them reliable and user-friendly.

Resolving conflicts in a product team requires open communication and empathy. For instance, I once navigated a disagreement over feature prioritization by facilitating a meeting where each member presented their perspectives and data-backed reasons, leading us to a consensus that best suited our company goals.

I measure the success of an AI product through various key performance indicators (KPIs) including user engagement metrics, customer satisfaction scores, and achievement of defined objectives and key results (OKRs). Regular assessments and feedback cycles are crucial for continuous improvement.

I typically embrace agile methodologies for product development, focusing on iterative processes that involve rapid prototyping and continuous feedback. This approach allows us to respond quickly to changes and adapt to user needs effectively, which is especially important in AI-powered products.

I stay updated with AI trends through various channels such as participating in industry conferences, reading research papers, engaging in online courses, and following influential thought leaders on social media. Networking with peers and experts also keeps me informed about emerging technologies and best practices.

To explain a complex AI concept to a non-technical stakeholder, I focus on simplifying the terminology and breaking down the process into relatable analogies. Using visuals and real-world examples helps clarify the concept while ensuring the stakeholder understands its implications for our product.

Customer feedback is central to my product decisions. It informs our roadmap and helps identify pain points that our AI Enrichment products must address. Regularly gathering and analyzing user feedback allows us to iterate and enhance product features effectively.

I approach cross-functional collaboration by fostering an inclusive environment where everyone feels valued in their contributions. Regular meetings and transparent communication help align teams, ensuring that engineering, design, and other departments work harmoniously towards common goals.

I believe the future of AI in product management will involve deeper integrations of AI-driven insights into the decision-making processes, enabling more personalized user experiences. AI will continue to evolve, and it will be crucial for product managers to adapt and leverage these advancements for strategic advantage.