Staff Product Manager, AI Agent Platform

As a Staff Product Manager within the Dash organization, you will define, build, and scale Dropbox’s agent platform & orchestration layer that powers intelligent assistants, tool agents, and workflow automations. You will lead both the strategic direction and hands-on execution of orchestration, planning agents, agent tooling, and democratized agent builder experiences.

A key focus will be developing a world-class, no-code agent builder experience that democratizes agent creation. You will empower Dropbox's SMB customers (many of whom don't have technical talent) to build and deploy agents that solve critical business issues. Simultaneously, you will build a robust internal platform that enables any team at Dropbox to build, deploy, and consume agents and tools, accelerating our internal AI development.

In this role, you’ll define the core abstractions and capabilities that make it easy for teams to create reliable, composable, and context-aware agents. You’ll partner closely with engineering, design, and applied AI to build a platform that scales from internal tools to developer-facing extensibility.

This is a highly technical and creative role for a PM who thrives on platform thinking, developer experience, and AI orchestration systems. You’ll translate complex technical opportunities into product strategies that empower others to innovate on top of Dropbox’s AI ecosystem.

• Define agent platform strategy and roadmap. Set long-term direction for orchestration layers, planner agents, tool agents, agent lifecycle, extensibility, and integration patterns.
• Drive execution and delivery across core agent infrastructure. Deliver planner modules, orchestration API, agent workflows, tool execution, scheduling, error handling, fallbacks, and scaling.
• Design and evolve a no-code / low-code agent builder experience. Provide visual UIs, templates, workflow editors, SDKs, integration connectors, and deployment tooling so non-technical users can build useful agents.
• Drive platform adoption and consumption across Dropbox. Enable internal teams to deploy, extend, or consume agents; foster best practices; integrate with product teams; provide APIs, documentation, and onboarding.
• Measure, monitor, and debug agent performance & reliability. Instrument agent execution, collect logs/traces/metrics, detect failures, handle retries and fallback paths, while driving continuous improvement.
• Collaborate cross-functionally to embed agents into user workflows. Partner with product, ML, design, operations, security, and infrastructure teams to align on UX, safety, data flow, and guardrails.
• Evangelize, mentor, and lead in agent culture and standards. Codify agent design guidelines, train internal teams, set guardrails (safety, cost, latency), and represent agent infrastructure in leadership forums.

• 10+ years of product management experience, with significant hands-on work in platform, tooling, orchestration, and internal infrastructure. Ideally candidate has experience operating as the DRI building products for other product teams or developers.
• Proven experience defining and shipping orchestration / workflow systems, agentic systems, or automation pipelines (planning, scheduling, execution).
• Strong technical fluency. Able to reason about APIs, event-driven systems, latency, error handling, reliability and distributed systems. Engages in deep technical discussions about system architecture, APIs, and technical trade-offs with engineers and data scientists.
• A strong sense of user empathy. Experience conducting user research and building products for both technical and non-technical audiences.
• Analytical mindset and instrumentation experience. Familiarity with logging, metrics, monitoring, error diagnosis, and performance optimization.
• Excellent cross-functional collaboration and influencing skills . Ability to drive consensus across engineering, ML, Product, Design, Ops, Security, etc,  with a proven ability to translate complex technical concepts and ambiguous problems into clear, structured product documents and compelling narratives.
• Bias toward quality, safety, and robustness. Experience defining guardrails, failure modes, fallback patterns, cost control, and  best practices in reliability engineering.

• Experience with no-code/low-code platforms or builder tools.
• Familiarity with modern AI agent frameworks and orchestration layers (e.g., LangChain, Semantic Kernel, Haystack).
• Experience building and scaling products for SMB customers.
• A background in applied data science, software engineering, or a related technical field.
• Experience with prompt orchestration, agent evaluation frameworks, human-in-the-loop correction, and reliability mechanisms.