Senior Technical Product Manager

ADP•Roseland, NJ

About The Position

ADP is building a next-generation AI-native HCM platform for small businesses. We are rethinking what payroll, HR, and compliance software looks like when it is designed from the ground up with Generative AI technology at the center. We are looking for a Senior Product Manager who is energized by building things, obsessed with customers, and already figured out how to get the most out of GenAI tools with your work, your personal and side projects, even just in the way you think about problems. You do not wait to be taught or told to adopt new products and technology. You pick it up, break it, learn from it, and figure out how to get the most out of it before anyone asks you to. In this role, you’ll work alongside a talented team of engineers, designers, and researchers to ship HCM capabilities that improve the everyday lives of small business owners. While you’re still earlyish in your career, you already have proof points that boost your credibility: things you shipped, problems you diagnosed, unique insights about the market or the customer that led to specific product pivots or new direction. You bring an optimistic, scrappy spirit and you elevate the people around you.

Requirements

Bachelor's degree or equivalent.
3+ years of firsthand experience defining and delivering digital products with agile teams, from discovery through launch.
Successfully, productively integrated GenAI / LLM tooling into professional workflows and are on top of the latest developments in the space.
Understand how large language models and AI-powered automation work well enough to have an informed opinion on when to use them and when not to.
Can articulate tradeoffs, not just possibilities.
Can engage and collaborate on technical matters with engineers, whether debating the merits of an A vs B approach to an API requirement or parsing an architecture diagram.
Bring depth to how you think about AI/LLM system behaviors.
Use data and client feedback to prioritize.
Can pull a report, interpret it, and act on it without being hand-held.
Effective communicator: can write a clear business case, run a productive meeting, and explain a technical constraint to a non-technical stakeholder.
Work well in (or even embrace) ambiguity.
Make progress without waiting for complete information, and course-correct quickly when new evidence arrives.
Naturally optimistic and energizing to work with.
Think of creative ways to solve problems and bring that energy to your team every day.
Can operate independently in tools like Jira, Confluence, or equivalent for planning, documentation, and tracking.

Nice To Haves

Technical, analytical, or design background a plus.
Bonus for hands-on experience in regulated domains like payroll, tax, HR, fintech, healthcare, where compliance, accuracy, and user trust are table stakes.
Have built and shipped something on your own: an app, a tool, a side project, especially using AI-assisted development.
Used LLM APIs, done prompt engineering, set up agentic work spaces or directories in a personal or professional project, not just used AI chatbots vanilla out of the box.
Experience with mobile or web development, even if not a full-time engineer.
Early adopter of the latest technology trends, a follower of influential technology personalities on social media, a reader of blogs or listener of technology podcasts.

Responsibilities

Work with engineering, design, and research teams daily to clarify priorities, unblock work, and keep things moving.
Contribute to new customer insights with UXR while debating pros and cons of an architectural decision with the engineering team.
Use client data, analytics, and curiosity to understand user needs.
Write sharp requirements and break down problems into testable increments.
Work positively and effectively with engineering, design, and business teams.
Share views, respectfully challenge decisions, and commit fully once a direction is set.
Instrument the product to monitor performance, pull metrics, and measure success to understand how to improve the product to reach desired business outcomes.
Stay close to real users by watching session recordings, reading support tickets, joining client calls, and asking questions that go beyond analytics data.
Form opinions about client needs, validate them with research, and steer the roadmap as needed.
Review or create AI-powered prototypes, write specs, and check survey results to advance the product.