Product Manager, Edelman Global AI

Edelman•New York, NY

10d•$60,000 - $85,000

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 this experience, helping client teams develop earned-first, data-backed strategy and creative. This hands-on, collaborative role works across 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 owns product priorities, roadmap, backlog, and requirements for earned-first strategy and creative workflows. It involves researching user behavior, translating complex agency processes into clear user experiences, aligning stakeholder needs, working with full-stack engineers throughout delivery, and identifying how generative AI, automation, data, and agentic workflows can create value. The Product Manager will prototype and pilot ideas, establish success measures, and use user feedback and data to continuously improve adoption and product performance.

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 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 use of AI tools.
Strong stakeholder research and management skills, including uncovering underlying needs, navigating perspectives, clarifying ambiguity, and building alignment across business and technical teams.
Strong user and UX instincts, with the ability to translate complex workflows into usable experiences and assess whether a product solves the right problem.
Experience in communications, PR, marketing, advertising, consulting, an agency, or another client-service environment, and understanding how client needs translate into strategy and deliverables.
Excellent communication, prioritization, and problem-solving skills 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 experience using Figma, Vercel v0, or other AI-assisted development environments.
Experience building internal enterprise products where adoption and change management are important.

Responsibilities

Define product priorities, roadmap, backlog, and requirements for earned-first strategy and creative workflows.
Conduct user interviews, workflow observation, pilots, and ongoing feedback research to identify needs, friction, and opportunities for technology to add value.
Translate complex 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 translate requests into scalable 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 valuable uses for generative AI, automation, and agentic workflows, and help define inputs, outputs, context, guardrails, human review, and evaluation approaches.
Define internal and third-party data needs and collaborate with engineering on APIs, integrations, schemas, and data pipelines.
Prototype ideas, pilot with real users, define success metrics, and iterate using qualitative and quantitative feedback.