Product Manager (Beyond Fuel)

WEXWEXUS•New York, DC

20h•$89,800 - $120,400•Hybrid

About The Position

WEX is transforming how businesses manage spend—with a vision beyond fuel through a growing set of payments and expense capabilities built on shared platform investments. We are looking for a curious, execution-driven early career Product Manager to help build and scale our next generation of payments solutions. You’ll build great products and own adoption, usage, and customer value—not just feature delivery. This role sits within the North American Mobility (NAM) Product Team and will focus on bringing new products to market, defining test-and-learn strategies, and owning features end-to-end. You will work closely with senior product leaders, engineering, design, and go-to-market teams to deliver solutions that customers actually use and love—not just features we ship. This is an ideal role for someone early in their product career who is hungry to learn, highly curious, and excited to leverage AI across the product development lifecycle.

Requirements

3+ years of experience in product management, consulting, startups, or a related field.
Strong curiosity and problem-solving mindset—you ask “why” and dig deeper.
Ability to break down ambiguous problems into clear steps and actions.
High empathy and experience or strong interest in customer research and interviewing.
Comfort working in a fast-paced, iterative environment.
Excellent communication and collaboration skills.
Actively use AI tools (e.g., Claude, ChatGPT, Cursor, copilots, prototyping tools) in your daily work.
Build and refine workflows, prompts, and lightweight automations.
Continuously experiment with how AI can improve product discovery, delivery, and decision-making.
Self-driven learning, side projects, or independent experimentation—including personal projects, coursework, or side hustles where you’ve explored how AI can improve workflows, productivity, or product thinking.

Nice To Haves

Fluency running GTM experiments and channel testing (email, in-product, sales-led).
Experience in payments, fintech, or expense management.
Familiarity with product analytics or experimentation.
Exposure to API-based products or technical systems.

Responsibilities

Own product features and adoption end-to-end: Support the development of new payments capabilities and workflows—from concept through launch and iteration to ensure they’re actually adopted.
Design and execute test-and-learn plans: Define experiments (e.g., fake door tests, betas, GTM validation) to validate customer demand, usage, and product-market fit.
Work directly with customers: Conduct interviews, participate in ride-alongs, and synthesize insights to inform product decisions. Analyze real customer behavior using data, research, and field insights especially to identify where customers drop off and why.
Translate customer problems into product requirements: Write clear, actionable requirements and partner with engineering and design to bring them to life.
Define platform priorities: Identify opportunities to simplify, standardize, and scale shared capabilities that can be leveraged across multiple products.
Build for reuse: Define APIs, services, integration patterns, and shared capabilities that make it easier for teams to launch new customer experiences without rebuilding common functionality.
Translate technical constraints into product decisions: Work with engineering to understand system limitations (e.g., payments, credit, integrations) and communicate them clearly to cross-functional stakeholders to inform scope, tradeoffs, and timelines.
Leverage AI across the product lifecycle (core expectation): Use AI tools to accelerate research and synthesis, prototype ideas and flows, analyze product and customer data, improve personal productivity and team output, continuously explore new ways AI can improve how we build products.
Partner cross-functionally: Work daily with engineering, design, data, sales, marketing, and servicing to deliver high-quality, customer-centric solutions.
Track and measure success: Define and monitor key metrics (adoption, usage, repeat behavior) and use data to inform decisions. Prove product-market fit through measurable behavior.