Product Manager, Edelman Global AI

Daniel J. Edelman•New York, NY

About The Position

Edelman is building AI-enabled products and workflows to help communications teams develop earned-first strategy. The Product Manager will own a core part of that experience, helping client teams develop earned-first, data-backed strategy and creative. This hands-on, collaborative role sits at the intersection of AI, product, and marketing, partnering with account teams, strategists, creatives, subject-matter experts, engineering, and design to understand workflows and turn user needs into intuitive, scalable products. The role involves owning priorities, roadmap, backlog, and requirements for earned-first strategy and creative workflows; researching user behavior; shaping user journeys and product experiences; aligning stakeholders; and working closely with full-stack engineering teams from requirements through launch. The Product Manager will also identify useful applications for generative AI, automation, and agentic workflows; define the data and integrations that support product experiences; and test and iterate products using pilots, success metrics, and user feedback.

Requirements

Approximately 3–5 years of relevant experience in product management, product ownership, digital product delivery, technology or solutions consulting, or a related role.
Experience owning technically complex software products or features from discovery and user research through delivery, adoption, and iteration, ideally working closely with full-stack engineering teams.
Strong product judgment and technical fluency, including the ability to discuss APIs, integrations, data flows, application architecture, and technical tradeoffs with engineers.
Hands-on familiarity with generative AI and modern AI product development beyond basic end-user use of AI tools.
Strong stakeholder research and management skills, including uncovering underlying needs, navigating different perspectives, clarifying ambiguity, and building alignment across business and technical teams.
Strong user and UX instincts, including the ability to translate complex workflows into usable experiences and evaluate whether a product solves the right problem.
Experience in communications, PR, marketing, advertising, consulting, agency, or another client-service environment, with an understanding of how client needs translate into strategy and deliverables.
Excellent communication, prioritization, and problem-solving skills, particularly in ambiguous, fast-moving environments.

Nice To Haves

Experience in earned media, corporate communications, communications strategy, or creative strategy.
Experience with media intelligence, social listening, audience or consumer insights, or other marketing and communications datasets.
Experience with third-party data integrations, APIs, and data pipelines.
Experience with AI-enabled workflow products, RAG, agents, LLM APIs, prompt or context design, or AI evaluation.
Hands-on design or prototyping using tools such as Figma, Vercel v0, and other AI-assisted development environments.
Experience building internal enterprise products where adoption and change management are critical to success.

Responsibilities

Define priorities, roadmap, backlog, and requirements for earned-first strategy and creative workflows.
Conduct interviews, workflow observation, pilots, and ongoing feedback to understand user behavior, friction, and opportunities for technology to create value.
Translate complex and variable agency workflows into clear user journeys and intuitive product experiences, partnering with UX and engineering on problem framing and ideation.
Build relationships across account teams, strategists, creatives, leadership, and technical partners; align competing needs and turn individual requests into scalable product priorities.
Translate user and business needs into requirements, user stories, and acceptance criteria, and partner with full-stack engineers through design, build, testing, and launch.
Identify where generative AI, automation, and agentic workflows can improve communications work; help define inputs, outputs, context, guardrails, human review, and evaluation approaches.
Define internal and third-party data needs for product experiences and collaborate with engineering on APIs, integrations, schemas, and data pipelines.
Prototype ideas, pilot with real users, define success metrics, and use qualitative and quantitative feedback to improve the product.