Senior Product Manager (Native AI, Core Experience)

EarnIn•Mountain View, CA

6h•Hybrid

About The Position

As a Senior Product Manager on the Core Experience (XP) team, you will own and evolve the foundational experiences that define how millions of EarnIn community members interact with the app every day. This role sits at the intersection of deep user empathy, systems-level product thinking, and a strong bias toward action, with AI as a first-class tool for making those experiences adaptive, personalized, and proactive. You'll shape the shared surfaces and journeys that span the entire app. This will be from how users navigate and discover value, to how the experience stays cohesive as EarnIn grows. Core XP is responsible for the holistic app experience, ensuring that key parts of the app bring product experiences together in a unified way. Your mission is to ensure these experiences are not only intuitive and cohesive but genuinely intelligent, such as using AI to surface the right value for the right member at the right moment, at a scale that static UX alone cannot achieve. This is a highly visible, cross-functional role requiring strong product judgment, AI fluency, and a deep appreciation for great UX. You will partner closely with design, engineering, data, ML, and leaders across Business Units to identify the highest-leverage opportunities and drive execution through focused experimentation. We're not looking for a PM who will bolt AI onto the roadmap; we need someone for whom AI is already embedded in the core of how they work, with repeatable systems and measurable impact to show for it. The base salary range for this full-time position is $206,000 to $252,000, plus equity and benefits. Our salary ranges are determined by role, level, and location. This is a hybrid position in Mountain View (Headquarters) and will require in-office work 2 days a week.

Requirements

4+ years of product management experience, ideally on consumer-facing or experience-heavy products.
A bachelor's degree in a related field or relevant experience.
AI fluency demonstrated in practice, not just on paper. We assess four dimensions: mindset (you use AI as a thought partner, not just a tool), strategy (you know which problems are worth solving with AI), building (you have repeatable AI-powered workflows — a spec process, a research synthesis pipeline, a structured pre-mortem — not one-off prompts), and accountability (you define what "good" looks like before you start, evaluate outputs critically, and own the result). We assess slope, not just a snapshot. Where you are on AI fluency matters. How fast you're moving matters more. We want to see a trendline: what you've tried, what you've abandoned, how your approach has evolved. Someone actively iterating is a different hire than someone who plateaued on the same three tools eight months ago.
Experience shipping personalized, adaptive, or AI-augmented consumer experiences. You know the difference between AI that feels magical and AI that feels creepy — and you design for the former.
Strong systems-level product thinking: you think in journeys, not features, and can hold the entire app experience in your head while improving one specific surface.
Highly organized and outcome-oriented, with the ability to manage complexity, dependencies, and competing inputs across multiple stakeholders.
Analytical but not rigid — you know when to rely on data, when to trust user insight, when to apply judgment, and when to use AI to synthesize across all three.
Deep empathy for financially underserved members — you build experiences that are genuinely helpful, never manipulative, and hold AI-powered personalization to the same standard.
Excellent communicator who can create clarity across design, engineering, data, and leadership — including in complex AI-driven tradeoff discussions where the right answer isn't obvious.

Nice To Haves

Experience building personalization systems, recommendation engines, or adaptive UX in consumer apps at scale is a plus.
Familiarity with responsible AI design for consumer surfaces: over-notification risk, filter bubbles, consent-forward personalization, and explainability is a plus
Experience leading a team's AI adoption — not just your own — through workflow redesign, clear expectations, and modeling the change you want to see is a plus.
Background in fintech, financial wellness, or products serving users with limited financial buffers is a plus
Experience upleveling team members with AI-native first-product thinking and design is a pleasure.

Responsibilities

Own the vision and roadmap for Core XP, home, navigation, explore, activity, and cross-product flows, with AI-native personalization and adaptivity as a first-class design principle, not an afterthought.
Define and ship AI-powered surface experiences: adaptive home layouts, contextual product discovery, predictive nudges, and smart in-app moments that respond to each member's real-time context.
Partner with design and data to move from static UX to living, responsive experiences — translating model capabilities into product moments members actually notice and trust.
Build and own an AI evaluation framework for Core XP surfaces: define quality benchmarks, set guardrails against over-personalization or intrusive AI behavior, and instrument feedback loops grounded in member outcomes — not just model metrics.
Use AI to accelerate your own discovery and experimentation loops — compressing the time from behavioral signal to actionable insight to shipped hypothesis.
Ensure Core XP surfaces remain intuitive and cohesive as new AI-powered products and capabilities are introduced across BUs.
Work horizontally across business units to surface experience gaps and align teams around shared solutions. This is a highly cross-functional role requiring buy-in and strong relationships with multiple stakeholders.
Bring structure, judgment, and calm to complex, cross-team decisions — balancing near-term engagement wins with long-term experience quality and member trust.
Improve how users find, understand, and move between EarnIn products through clearer navigation, AI-informed content hierarchy, and better contextual cues.
Articulate product direction, AI strategy, and tradeoffs in a way that builds trust and alignment across teams and leadership.