Product Manager II

F5 F5 · Enterprise · Seattle, WA +1

Product Manager II at F5 to own the AI model ecosystem, token economy, and core agentic platform enablement. This role involves end-to-end management of the LLM stack, developer-facing AI resources, and token economics, supporting F5's agentic transformation by building tools, documentation, and developer experience for secure and scalable AI agents. Requires strong analytical skills, technical curiosity, and passion for LLM and agentic software frameworks, with a focus on product execution and developer enablement.

What you'd actually do

  1. Own the lifecycle of AI models within F5, evaluating, onboarding, and managing access to the latest foundational models (e.g., Gemini, OpenAI, open-source models).
  2. Serve as the product owner for developer-facing tooling, SDKs, and APIs that facilitate agentic AI development.
  3. Own the enterprise token economy: track usage patterns, forecast capacity, and develop optimized pricing and chargeback models.
  4. Ensure model access and agent integrations adhere to strict corporate security, privacy, and data governance policies.
  5. Manage and prioritize the backlog for model hosting, API routing, token metrics, and developer enablement tools.

Skills

Required

  • 3+ years of Product Management experience delivering developer platforms, APIs, SaaS, or technical infrastructure.
  • Strong working knowledge of generative AI fundamentals (LLMs, API integrations, context windows, token consumption, and model routing).
  • Familiarity with agentic concepts (e.g., tool-calling, agent frameworks, MCP, orchestrators) and a desire to help developers build agents.
  • Highly analytical with experience monitoring technical metrics, usage data, cloud spend, or subscription economics.
  • Excellent technical communication skills, with the ability to build trust with engineering teams.

Nice to have

  • Experience with developer platforms, technical documentation, or internal developer relations (DevRel).
  • Understanding of cloud governance, FinOps, or managing usage costs for API platforms.
  • Hands-on experience with AI development orchestration tools (e.g., LangChain, LlamaIndex) or secure hosting platforms (Gemini, Azure AI, AWS Bedrock).

What the JD emphasized

  • agentic transformation
  • agentic AI development
  • multi-agent workflows
  • agent deployment
  • enterprise token economy
  • token economics
  • token consumption
  • token-tracking model
  • security
  • data governance policies
  • governance
  • cost controls
  • shadow AI
  • secure, internal ecosystem

Other signals

  • AI model ecosystem
  • token economy
  • agentic platform enablement
  • LLM stack
  • developer-facing AI resources
  • agentic transformation
  • multi-agent workflows
  • responsible AI
  • governance