Description

Position at Fingerpaint Group

Team Overview

The Product & Applied AI team is a dedicated group focused on transforming our business by building unique Fingerpaint solutions and evolving our ways of working. In partnership with the business, we build the foundations, software, agents, tools, and workflows that will empower the broader agency to achieve its business goals and deliver strategic and imaginative work.

Role Overview

The Product Manager, Applied AI, is a strategic conduit between the business and the agency's AI product engineers for one or more products. You partner with business sponsors to deeply understand the problem, document requirements, and translate business needs into clear specifications that technical teams can build against.

This role serves as a central connector between technical execution and business strategy. You build BRDs and PRFAQs, manage the product backlog, and own the product lifecycle from documented requirement through launch and adoption for your product or products, ensuring we deliver solutions that drive measurable value.

Please note that this is a hybrid role that requires 2 days per week onsite in Philadelphia, PA.

Duties and Responsibilities

Product Strategy & Roadmapping

• Business Partnership: Build and maintain relationships with Business Sponsors. You are responsible for deeply understanding the problem behind each priority and documenting it clearly.
• Requirements Discovery: Conduct interviews with Business Sponsors and their teams to translate stated needs ("this takes too long") into documented problems, requirements, and features ("we need an agent to automate reference checking, with X inputs and Y outputs").
• BRD Ownership: Write Business Requirement Docs as the core artifact connecting business intent to technical build. Maintain the backlog of documented requirements and feature updates in partnership with Business Sponsors.
• Product Roadmap Development: Develop and maintain the product roadmap, envisioning current and future versions and defining modular builds where applicable. Validate roadmap direction with Business Sponsors to confirm business value and with Engineering to confirm feasibility before committing.

Execution & Delivery

• Timeline Management: Establish, own, and communicate project timelines across the product lifecycle, from requirements through launch. Proactively flag schedule risks to Business Sponsors and Engineering, and adjust sequencing as priorities or capacity shift.
• Engineering Tasking: Manage day-to-day engineering tasking related to product build-out, sequencing work against capacity and priority.
• Technical Partnership: Partner with Product Applied AI Engineers to review and approve technical requirements in accordance with the BRD. Ensure build matches specs.
• Agile Leadership: Lead the agile development process (Sprint Planning, Standups, Retrospectives), serving as the primary point of contact between Business Sponsors and engineering to clarify specs and unblock decisions.
• Dependency Management: Manage cross-team dependencies and sequencing across Applied AI Engineering, Data Engineering, IT, and other partner teams.
• Build vs. Buy: Keep apprised of the market to consider off-the-shelf tools when applicable.

Adoption & Change Management

• Rollout Partnership: Partner with Business Sponsors to lead rollout, including co-developing training materials and documentation to drive adoption.
• Metrics Ownership: Define success metrics for each product at launch. Monitor usage and satisfaction data on an ongoing basis to inform backlog prioritization and feature updates.
• Feedback Loops: Establish channels for user feedback with Business Sponsors to iterate on live products.
• Commercialization: Collaborate with Client Service teams to package successful internal tools into client-facing offerings where appropriate.

Governance & Compliance

• Maintain general working awareness of data privacy, security, and regulatory considerations relevant to AI products. Flag potential policy or compliance concerns early in the requirements process and escalate to Legal/Operations for review.

Requirements and Experience

• Minimum of 5-7 years of experience in Product Management, preferably within a digital agency, marketing technology, or SaaS environment.
• AI Fluency: Strong understanding of LLM capabilities and limitations, with the ability to make informed trade-offs between cost, speed, and quality. Coding skills are not required.
• Data Literacy: General fluency in data concepts, including pipelines, data quality, and structure, sufficient to scope feasibility conversations with Engineering and Data teams. Deep technical data skills are not required.
• The Method: Experience with Agile/Scrum methodologies and proficiency with product management tools.
• The Industry: Experience working in regulated industries (healthcare/pharma) is highly preferred.
• Soft Skills: Exceptional ability to manage without authority, rallying cross-functional teams around a shared vision.
• Data-Driven: Comfort with analytics; ability to define success metrics and pivot product strategy based on performance data.

Role Performance Metrics

• Adoption rate across shipped products
• Backlog velocity / cycle time from BRD to launch
• Stakeholder satisfaction (Business Sponsor feedback)
• Number of products successfully commercialized

Don't meet every single requirement? That's okay! Studies have shown that women and people of color are less likely to apply to jobs unless they meet every single qualification. At Fingerpaint, we are dedicated to building a diverse, inclusive, and authentic workplace, so if you're excited about this role but your experience doesn't align perfectly, we encourage you to apply anyway. You may be just the right candidate for this or other roles! Our team of qualified recruiters can match you with the right opportunity.