Staff Product Manager, AI Infrastructure and Compliance

Box•Redwood City, CA

9h•$231,000 - $288,500•Hybrid

About The Position

Enterprise customers want to unlock the power of AI while maintaining the security, governance, compliance, and administrative controls they expect from Box. As AI agents become capable of accessing enterprise content and taking actions across business workflows, these capabilities become even more critical. We’re looking for a Staff Product Manager to lead AI Infrastructure and Compliance — a foundational product area for delivering enterprise-grade AI and enabling some of Box’s most strategic customers to adopt AI at scale. You will define how organizations govern AI across Box: how AI activity is permissioned, stored, audited, and controlled; how agents are protected against AI-specific security risks; how administrators set guardrails and model policies; and how Box AI meets demanding regulatory and compliance requirements such as FedRAMP, DoD Impact Levels, and Export Control. You will also shape how AI integrates with Box’s existing Governance and Shield capabilities so customers can extend the policies they already trust to AI-powered experiences. This is a broad and technically complex product area that sits at the intersection of AI, security, content permissions, governance, and platform architecture. You’ll work closely with architects, engineering leaders, security and compliance teams, and product teams across Box to establish common capabilities that can be consistently applied across Box AI experiences. If you enjoy solving technically deep platform problems, bringing clarity to ambiguous spaces, and aligning teams around architectural decisions that unlock major customer opportunities, this role is for you.

Requirements

7+ years of product management experience, including significant experience owning technically complex platform, security, governance, compliance, infrastructure, or enterprise products.
A strong technical foundation and can engage deeply with architects and senior engineers on system architecture, APIs, identity and permissions, data models, and platform trade-offs.
Understand enterprise security, governance, and compliance and can translate complex requirements into scalable product capabilities rather than one-off solutions.
Experience with, or a strong understanding of, AI/ML systems and emerging AI security risks, particularly those associated with agents, tool use, permissions, and autonomous actions.
Comfortable navigating complex systems involving content storage, permissions, identity, authorization, auditability, and policy enforcement.
Demonstrated success driving products that require coordination across multiple engineering and product teams, where ownership and technical dependencies extend beyond a single team.
Ability to operate effectively at Staff level: defining strategy in ambiguous spaces, identifying the most important problems, making difficult prioritization decisions, and influencing leaders without relying on organizational authority.
An exceptional communicator who can translate complex technical and compliance topics into clear decisions for engineers, customers, executives, and other stakeholders.
Experience working directly with large enterprise customers and understand the security, governance, and administrative requirements that influence enterprise technology adoption.

Nice To Haves

Experience with FedRAMP, DoD impact levels, export controls, data governance, DLP, or security policy platforms is a strong plus.
Experience building AI agents, AI platforms, security or compliance products, or enterprise content systems is a strong plus.
You approach your work with a growth mindset and actively leverage AI to make faster, smarter decisions and increase your impact.

Responsibilities

Own the strategy and roadmap for AI Infrastructure to support that AI has the right AI Admin, Governance & Compliance, defining the foundational controls enterprises need to deploy AI and agents securely and at scale.
Define how AI sessions and agent activity are permissioned, stored, and governed across Box products, including experiences such as Box Automate.
Build enterprise-grade auditability and observability for AI, enabling customers to understand and govern how users and agents interact with enterprise content.
Define Box’s Agent platform approach for handing AI security use cases.
Build administrative controls for model selection and policy enforcement, giving organizations control over which AI models can be used based on their security, compliance, and business requirements.
Partner with Security, Legal, Compliance, Product and Engineering to meet requirements including FedRAMP, DoD Impact Levels, Export Control, EU AI Act, and other enterprise and government standards.
Partner with SEC Product to define how existing Box Governance and Box Shield policies extend to AI and agent experiences, creating a consistent governance model across content, users, and agents.
Establish common platform capabilities and policies that work consistently across Box agents, Box Automate, and third-party agents accessing Box through MCP.
Partner deeply with enterprise architects and engineering leaders on complex areas including Box’s file system, permissions, agent identity and authorization, and AI security architecture.
Drive alignment across multiple product and engineering organizations, resolving architectural and product trade-offs and establishing clear ownership across shared platform capabilities.
Work directly with strategic enterprise customers and GTM teams to understand AI governance requirements, unblock adoption, and translate customer needs into scalable platform capabilities.
Communicate strategy, architectural trade-offs, roadmap priorities, and outcomes clearly to executives and cross-functional stakeholders.
Manage models and lifecycles for models to ensure model neutrality and compliance for our customers.