Agent Product Manger

TitanSan Francisco, CA
$185,000 - $250,000

About The Position

As an Agent Product Manager, you get Titan's AI agents working in our enterprise clients. You learn each environment, map the systems and workflows, encode client policies, and stand agents up in production, then tune them until they're resolving real work reliably. This is a hands-on, technical role that sits between product and the field: your job is to take agents from "configured" to "trusted and resolving tickets at scale," and to turn what you learn into a better product. You work closely with Forward Deployed Engineers, who own the overall relationship, while you drive the agent deployment itself, from initial integration through tuning, measurement, and expansion across new workflows.

Requirements

  • 3+ years in a Product Management, Forward Deployed Engineer, Solutions Architect, or similar deployment-focused role.
  • Hands-on and technical: proficient with scripting and APIs, with the aptitude to learn identity, cloud, and security/endpoint tooling.
  • Fluent alongside AI tools, and able to design and tune AI-native workflows.
  • Comfortable with ambiguity and speed. You'd rather ship and iterate than wait for a perfect spec.
  • Detail-driven and reliability-minded: you care that agents work correctly in production, not just in a demo.

Responsibilities

  • Deploy AI agents in client environments: integrate Titan with each customer's tooling, encode their policies, and get agents resolving work in production.
  • Tune for reliability: monitor agent performance, debug failures, and iterate on prompts, workflows, and guardrails until resolution quality and trust are high.
  • Map systems and workflows: learn each client's service desk, identity, cloud, security, and endpoint stack, and design how agents fit into it.
  • Expand coverage: identify new workflows and ticket types agents can take on, and roll them out with minimal disruption.
  • Turn field learnings into product: partner with Engineering to make deployment faster and more repeatable, and feed real-world findings back into the platform and roadmap.
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