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Salary: USD 102,100 - 153,100 / annual
F5 Digital is seeking a Product Manager II to own the company's AI model ecosystem, token economy, and agentic platform enablement. This role manages the end-to-end lifecycle of F5's LLM stack, developer-facing AI resources, and token economics, serving as a critical bridge between platform engineering, security, finance, and internal development teams.
Key responsibilities include:
Model Ecosystem Management: Own the evaluation, onboarding, and management of foundational AI models (Gemini, OpenAI, open-source alternatives). Partner with platform engineering to ensure secure, observable integration into developer environments. Maintain deep knowledge of the evolving LLM landscape to guide architectural decisions.
Agentic Transformation & Developer Enablement: Serve as product owner for developer-facing tooling, SDKs, and APIs that facilitate agentic AI development. Support teams in transitioning from prompt engineering to complex multi-agent workflows. Create high-quality developer resources, sample code, and onboarding paths to accelerate internal agent deployment.
Token Economics & Platform Efficiency: Own the enterprise token economy by tracking usage patterns, forecasting capacity, and developing optimized pricing and chargeback models. Define and track key metrics including model latency, token efficiency, usage anomalies, and cost-per-query. Partner with Finance and Cloud FinOps to manage AI spend while scaling capacity.
Governance & Responsible AI: Ensure model access and agent integrations adhere to corporate security, privacy, and data governance policies. Implement guardrails, logging patterns, and cost controls to reduce model risk and mitigate shadow AI.
Product Execution: Manage backlog prioritization for model hosting, API routing, token metrics, and developer enablement tools. Lead Agile sprints and collaborate closely with systems, platform, and security engineers.
Required: 3+ years of product management experience with developer platforms, APIs, SaaS, or technical infrastructure. Strong knowledge of generative AI fundamentals (LLMs, API integrations, context windows, token consumption, model routing). Familiarity with agentic concepts (tool-calling, agent frameworks, MCP, orchestrators). Highly analytical with experience monitoring technical metrics, usage data, cloud spend, or subscription economics. Excellent technical communication skills and ability to build trust with engineering teams.
Preferred: Experience with developer platforms, technical documentation, or internal developer relations. Understanding of cloud governance, FinOps, or managing API platform costs. Hands-on experience with AI orchestration tools (LangChain, LlamaIndex) or secure hosting platforms (Gemini, Azure AI, AWS Bedrock).
