Senior Product Manager, AI Agent Orchestration

Box•Redwood City, CA

1d•Hybrid

About The Position

Box AI is transforming the way businesses manage and leverage content by incorporating cutting-edge artificial intelligence and machine learning capabilities into the Box Content Cloud. As a Senior Product Manager for Box AI Agents, you will play a key role in building the next frontier of intelligent content management, leading AI-driven solutions that revolutionize how enterprises interact with their content. In this role, you will be at the helm of driving Box’s AI platform strategy, execution, and iteration, shaping the future of enterprise AI solutions. You’ll define and execute product roadmaps that leverage AI technologies, such as large language models (LLMs) and retrieval-augmented generation (RAG), to unlock insights, automate workflows, and improve collaboration across global enterprises. Your work will directly impact how businesses across the world manage and extract value from their content at scale. If you're passionate about defining and leading AI product strategies, bringing AI solutions to market, and driving real-world business impact, this is your chance to lead a high-impact role in the next chapter of Box’s AI growth.

Requirements

Proven track record of launching successful AI-powered products at scale, with experience in enterprise or consumer AI applications that are used in the market today.
Experience in AI product management, with expertise in large language models (LLMs), retrieval-augmented generation (RAG), vector databases, and AI evaluation frameworks.
Strong product management rigor, with experience in user research, defining and tracking product metrics, and delivering measurable results.
Strong technical background, with experience working with data scientists, machine learning engineers, and cross-functional teams to bring AI solutions to market.
Experience with prompt engineering, supervised fine-tuning (SFT), and other fine-tuning techniques for AI models.
Well-versed in different market LLMs and their strengths and weaknesses, enabling informed decisions on model selection.
Comfortable driving product strategy, starting small, iterating quickly, and scaling AI products to deliver enterprise-grade solutions.
Deep knowledge of enterprise SaaS products, with the ability to understand and deliver on the unique needs of enterprise customers.
Experience collaborating with engineering teams to design and deliver AI-driven content management solutions.
A minimum of 4+ years of product management experience in AI/ML, enterprise SaaS, or cloud platforms.
A technical degree in Computer Science, Mathematics, or related fields, with practical experience in AI, machine learning, or cloud infrastructure.

Responsibilities

Lead the strategy and long-term architecture for Box's core AI orchestration platform — the foundational layer that powers how AI agents reason, plan, and act across the entire Box product surface.
Define and own a technically complex, mission-critical product area at the intersection of AI infrastructure and enterprise-grade content workflows, balancing the needs of internal platform teams, external developers, and enterprise customers.
Drive the next generation of agent architecture, anticipating how advances in AI reasoning, multi-step planning, and compute paradigms will reshape what's possible — and translating that vision into a concrete, sequenced roadmap.
Serve as the connective tissue across every team building on the AI platform — establishing shared primitives, coordinating dependencies, and ensuring that foundational architectural decisions scale gracefully as adoption grows.
Lead end-to-end product development for the orchestration layer: from identifying capability gaps and architectural constraints to shipping production-grade solutions and iterating based on real-world usage signals.
Collaborate deeply with engineering and applied AI teams to design and evolve the systems that govern how tools are invoked, how context is managed, and how agents coordinate across complex, multi-turn workflows.
Establish a rigorous, metrics-driven approach to platform health and capability maturity — defining the right signals to measure reliability, latency, and quality at scale across diverse enterprise use cases.
Partner cross-functionally with teams across features, infrastructure, and go-to-market to ensure the platform's capabilities are well-understood, well-documented, and effectively leveraged by every team building on top of it.
Stay at the leading edge of the AI agent landscape — continuously evaluating emerging patterns in orchestration, tool use, and agentic compute — and bringing that perspective to bear on Box's platform strategy.