Staff Product Manager, AI Security

Box (NYSE:BOX) is the leader in Intelligent Content Management, founded in 2005 and headquartered in Redwood City, CA. As a Staff Product Manager for AI Security, the individual will be the strategic product leader responsible for defining and executing the product vision and roadmap to secure agentic AI capabilities, autonomous workflows, and generative AI integrations across the Box Intelligent Content Management platform. This is a high-impact individual contributor role building and scaling defense mechanisms for Box's native agentic capabilities, including Box Agent, and external integrations connecting third-party agents and foundation models via Model Context Protocol (MCP) and enterprise APIs.

Responsibilities

Define and execute the product strategy, technical vision, and roadmap for AI Security and Agentic Guardrails across Box AI, Box Shield, and the broader Box platform ecosystem; Build agent guardrail frameworks and policy engines to monitor, evaluate, and constrain autonomous agent behaviors across Box Agent, custom workflow agents, and external model integrations; Secure agentic connectivity powered by Model Context Protocol (MCP) and third-party AI APIs, establishing strict authentication, context boundary isolation, dynamic permissioning, and secure tool execution; Architect multi-layered defenses against advanced AI threats, including direct and indirect prompt injection, jailbreaking, training data extraction, system prompt leakage, and coordinated agentic attack swarms; Partner with Engineering, Applied AI/ML Research, Security Architecture, and UX Design to deliver low-latency, enterprise-grade AI security controls; Drive key business and security efficacy metrics, including guardrail evaluation accuracy, prompt injection prevention rates, MCP integration adoption, and Shield / Enterprise Plus security revenue growth; Collaborate with Product Marketing, Sales, Customer Success, and Compliance to lead GTM strategy; Engage directly with enterprise customers, AI security working groups, and industry analysts to anticipate evolving AI attack vectors, validate product requirements, and guide industry best practices

Requirements

8+ years of product management experience building and scaling enterprise B2B SaaS security products, cybersecurity platforms, cloud security solutions, or AI/ML infrastructure platforms; Deep domain expertise in AI/ML security, LLM application security (e.g., OWASP Top 10 for LLM Applications), prompt injection defense, agentic guardrail frameworks, or model alignment and safety systems; Proven track record developing product strategies around agentic architectures, multi-agent coordination, tool-use and function-calling security, or model integration protocols such as Model Context Protocol (MCP); Strong understanding of emerging threat vectors targeting autonomous AI systems, including multi-turn adversarial attacks, indirect injection via ingested content, and coordinated agentic attack swarms; Technical acumen to partner with AI/ML research and engineering leaders on vector embeddings, semantic evaluation models, LLM latency trade-offs, API gateway security, and zero-trust data access control; Exceptional analytical capability to define guardrail telemetry and track threat mitigation efficacy; Executive presence to influence C-level security leaders and align cross-functional stakeholders; Boxers are expected to work from their assigned office a minimum of 3 days per week

Nice to have

Experience working with frontier AI/LLM models, prompt evaluation frameworks, red-teaming AI systems, or developing real-time guardrail runtime libraries (e.g., NeMo Guardrails, Llama Guard, or proprietary guardrail pipelines); Hands-on familiarity with MCP (Model Context Protocol), agent orchestration frameworks, or semantic router architectures; Familiarity with enterprise compliance standards, zero-trust architectures, data loss prevention (DLP), or AI governance frameworks (e.g., NIST AI RMF, ISO 42001); Technical background with a Bachelor's or Master's degree in Computer Science, Cybersecurity, Artificial Intelligence, Engineering, or equivalent practical experience

Benefits

Equity; Benefits and perks