Product Manager, Reputation Marketing & Insights

Amazon Amazon · Big Tech · NY +1 · Project/Program/Product Management--Technical

Product Manager for internal applications and operational platforms that streamline workflows across Reputational Marketing & Insights (RMI). The role involves owning product strategy, roadmap, and delivery, evaluating and leveraging AI/ML tools, LLMs, and agentic frameworks, defining technical requirements, and building tools to change what's possible. The focus is on delivering internal AI-powered development tools and LLM-based agents.

What you'd actually do

  1. Define the product and technology strategy for the team's internal tools ecosystem.
  2. Own a portfolio of applications that serve as the operational backbone of a fast-moving marketing organization — from audience management and campaign budgeting to media measurement and workflow automation.
  3. Evaluate and leverage AI/ML tools, large language models, and agentic frameworks to accelerate development and augment team capabilities — understanding the strengths, limitations, and appropriate use cases for each.
  4. Define technical requirements — including APIs, data integrations, cloud architecture, and AI-assisted workflows — and articulate when a new technology is needed (and when it is not).
  5. Build tools that change what's possible.

Skills

Required

  • Product strategy and roadmap definition
  • Feature delivery and tradeoffs
  • Engineering discussions and technology decisions
  • Managing technical products or online services
  • Advocating for customers and stakeholders
  • Machine Learning and Large Language Model fundamentals
  • Cloud services (AWS), databases, APIs, and scripting languages

Nice to have

  • Data warehouse technical architecture
  • Kubernetes, Docker or containers ecosystem
  • Software development
  • Influencing senior leadership
  • Managing complex customer relationships
  • Building internal tools or platforms using rapid-development frameworks (Streamlit, Retool, or similar)
  • AI coding assistants, agentic development frameworks, or LLM-based automation
  • Driving adoption of internal products
  • Public affairs, communications, or marketing environments

What the JD emphasized

  • own the product strategy, roadmap, and delivery
  • define the product and technology strategy
  • own a portfolio of applications
  • Product strategy, feature design, and technology approach are yours to define
  • deliver independently with limited guidance
  • identify where manual processes create drag and define product solutions that scale
  • evaluate and leverage AI/ML tools, large language models, and agentic frameworks
  • align stakeholders across competing priorities
  • define technical requirements
  • articulate when a new technology is needed (and when it is not)
  • influence the strategic direction of how the team operates
  • accountable for product adoption, process efficiency gains, and stakeholder satisfaction
  • develop mechanisms to capture voice-of-customer feedback from internal users and translate it into a prioritized product roadmap
  • define product strategy and own the full lifecycle for a portfolio of internal tools
  • build web applications and data integrations using AWS
  • evaluate and deploy AI-powered development tools and LLM-based agents
  • drive stakeholder alignment across competing priorities
  • make independent architecture decisions
  • automate processes that depend on individual heroics
  • operationalize analytical outputs into production-ready tools accessible to non-technical users
  • Experience owning/driving roadmap strategy and definition
  • Experience with feature delivery and tradeoffs of a product
  • Experience contributing to engineering discussions around technology decisions and strategy related to a product
  • Experience managing technical products or online services
  • Experience in representing and advocating for a variety of critical customers and stakeholders during executive-level prioritization and planning
  • Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience leading and influencing your team or organization
  • Demonstrated ability to work hands-on with cloud services (AWS), databases, APIs, and scripting languages at a practitioner level
  • Experience building internal tools or platforms using rapid-development frameworks (Streamlit, Retool, or similar)
  • Hands-on experience with AI coding assistants, agentic development frameworks, or LLM-based automation (e.g., Bedrock Agents, Claude, autonomous coding tools)
  • Track record of driving adoption of internal products through strong voice-of-customer practices and iterative improvement