Product Manager, Agent Studio

Sierra Sierra · AI Frontier · San Francisco, CA · Product

Product Manager for Agent Studio, the core environment for creating, testing, and improving AI agents. The role involves defining the agent building experience, owning the development lifecycle, building simulation and testing systems, designing reusable components, integrating AI copilots, and making agent quality measurable.

What you'd actually do

  1. Define the agent building experience - Shape how users move from idea → implementation across journeys, chat, and workflows. Create clear abstractions for building complex agent behavior without unnecessary friction.
  2. Own the Agent Development Life Cycle - Design how users analyze conversations, make changes, test improvements, and release updates. Ensure the loop between build → test → learn is tight, fast, and intuitive.
  3. Build simulation and testing systems - Define how agents are validated before deployment. Create tools for simulating real-world scenarios, identifying failures, and improving performance with confidence.
  4. Design reusable systems through packages - Define how integrations, skills, and agent behaviors are packaged, discovered, and reused. Enable users to compose sophisticated agents from modular building blocks that improve over time.
  5. Integrate AI copilots into the workflow - Work closely on how Ghostwriter (build) and Explorer (analyze) fit into Agent Studio. Decide what is automated vs user-driven, and how AI augments each step of the workflow.
  6. Make agent quality measurable and actionable- Define evaluation frameworks and feedback systems so users can understand performance and systematically improve their agents.

Skills

Required

  • 3+ years of product management experience
  • Experience building 0→1 products or platforms
  • Experience working with AI systems
  • Strong product instincts for builder tools

Nice to have

  • working on developer platforms
  • AI systems
  • complex technical products
  • Strong technical depth
  • Ability to engage deeply with engineers on system design
  • simulation systems
  • evaluation frameworks
  • APIs
  • platform architecture
  • Experience building 0→1 products or platforms
  • Comfortable defining new abstractions and workflows in ambiguous spaces
  • Familiarity with LLMs
  • challenges of building, testing, and iterating on non-deterministic systems

What the JD emphasized

  • zero-to-one
  • scaling role
  • developer platforms
  • AI systems
  • complex technical products
  • Strong technical depth
  • system design
  • simulation systems
  • evaluation frameworks
  • platform architecture
  • building 0→1 products or platforms
  • ambiguous spaces
  • AI systems
  • LLMs
  • non-deterministic systems
  • builder tools

Other signals

  • agent development lifecycle
  • building agent platforms
  • integrating AI copilots