Senior Product Manager

Menlo Security is the leader in Browser Security for human and agentic workforces. Our mission is to enable humans and agents to connect, communicate, and collaborate securely, without compromise. The Menlo Browser Security Platform protects organizations from cyberattacks by stopping threats across the web, documents, and email before they reach the user. With Menlo Agent Runtime Security (MARS), that protection now extends to the AI agents working alongside every employee. Menlo Security is trusted by major global businesses, including Fortune 500 companies and government agencies, to protect their most valuable asset, their data, and is backed by top-tier investors. About the Role Summary Menlo Security is building MARS for Agents (Menlo Agent Runtime Security), our product line for securing autonomous and hybrid AI agents. This is a category still being defined — standards, architecture patterns, and competitive positioning are all forming in real time, with competitors ranging from established network security vendors to a wave of new agent-security startups. We are hiring an experienced Product Manager / Product Owner to take end-to-end ownership of a significant, technically complex area within MARS for Agents. The specific scope will be defined in partnership with the hiring manager based on team needs and the background of the person in this role, and will span identity and security concepts, relevant technical protocols, and platform integration and partnership work. The role operates with a high degree of autonomy day to day, working from strategic direction set by the Head of Product, in an environment that runs agile development at high velocity while actively building the process and rigor needed to scale a growing product line. This is also a team that works the way it builds: AI assistants and LLM-based tools are part of the daily toolkit here — used to synthesize customer and competitive signal, pressure-test requirements, and prototype against MCP clients and agent runtimes before a single line of production code is written. The person in this role will be defining security for a category they are already a fluent, curious user of. Outcomes & KPIs Key Outcome(s) Owned:

• End-to-end ownership of an assigned surface area of MARS for Agents — across capabilities such as the agent registry, Claude integration, Microsoft Copilot integration, MCP Server, MCP Proxy, and LLM proxy — from researched opportunity, to written requirement, to shipped and supported capability.
• A current, honest, decision-changing competitive point of view for the agent-security category that the wider go-to-market organization can rely on. Success Metrics / KPIs
• Roadmap delivery: committed roadmap items for the owned surfaces shipped within the target release window.
• Requirements quality: Reduction in mid-sprint requirement clarifications and rework attributable to ambiguous PRDs or acceptance criteria, measured via engineering feedback each quarter.
• Enablement coverage: 100% of shipped capabilities in the owned area have current capability documentation and a delivered briefing to support and solutions engineering at or before release.
• Adoption of shipped capability: Customer adoption or usage of newly released capabilities against a target set at launch, tracked for 90 days post-release.
• Competitive influence: At least one documented roadmap or positioning decision per quarter, traceable to a published competitive finding. What You'll Do
• Own inbound product direction for your area. Research emerging agentic AI capabilities, attacker techniques, and adjacent standards (MCP, A2A, OWASP agentic-security guidance, agent identity frameworks) to determine what MARS for Agents should build next across the agent registry, Claude integration, Microsoft Copilot integration, MCP Server, MCP Proxy, and LLM proxy.
• Turn signal into engineering-ready requirements. Translate market, customer, and competitive input into clear PRDs, user stories, and acceptance criteria — using LLM-based tools to synthesize call notes, support tickets, standards documents, and usage data into prioritization insight, while retaining full accountability for the judgment calls and the accuracy of what you write.
• Own and groom the backlog. Make day-to-day prioritization calls across your surfaces within the strategic guardrails set by the Head of Product, and partner directly with engineering through the full build cycle: refinement, in-sprint questions, review, and release.
• Validate before you specify. Use AI coding assistants, MCP clients, and agent runtimes hands-on to prototype and stress-test proposed behavior — so requirements are grounded in how agents actually behave, not just how they are documented to behave. Define success metrics for what you ship and track them post-release.
• Enable the field. Brief technical support and solutions engineering on new and existing capabilities, and maintain current capability documentation for your area that clearly separates documented and shipping facts from planned work and open questions, so the field never over-promises. Be the trusted authority on what your part of MARS does today, what is coming, and what it deliberately does not do yet.
• Engage customers, sales, and marketing. Join customer and prospect conversations periodically to gather requirements, pressure-test positioning, and support technical evaluations; support the sales team with technical Q&A, competitive objection-handling, and input on proposals and decks; and work with product marketing on messaging, positioning, and launch content.
• Run competitive analysis that changes decisions. Continuously track competitors relevant to MARS for Agents — network/SSE-SASE incumbents (Palo Alto Networks, Zscaler, Cloudflare, Netskope), agent-identity and IAM players (Okta, CyberArk), MCP gateway vendors, and emerging agent-security pure-plays — and maintain a clear point of view on where MARS leads, where it currently trails, and what capabilities are commoditizing. Feed those findings directly into requirements, positioning, and roadmap prioritization. Functional Competencies Required:
• 6–10+ years of product management or product owner experience, ideally in B2B SaaS, enterprise infrastructure, or security software, including a track record of owning a complex, technical product area end to end.
• Demonstrated ability to write clear, engineering-ready requirements (PRDs, user stories, acceptance criteria) and to own a backlog end to end for a technically complex product surface.
• Comfort operating with a high degree of autonomy. This role receives strategic direction rather than daily instruction, and the person in it should be able to take a goal and drive it through research, requirements, engineering partnership, and launch across multiple related surfaces at once — with the support of a collaborative product and engineering team.
• Comfort operating at high velocity. Our engineering organization runs agile at a fast cadence, and this role also helps bring the process and rigor needed to make the product scalable, so both muscles matter.
• Solid working knowledge of AI agent technology: how LLMs and AI agents operate, the difference between autonomous and human-in-the-loop (hybrid) agents, tool and function calling, and — specifically — the MCP (Model Context Protocol) ecosystem (servers, clients, tool calls) at a depth sufficient to write requirements for an MCP Server and an MCP Proxy, not just discuss them conceptually.
• Real cybersecurity background, with working familiarity in areas such as identity and access management, proxy and gateway architectures (forward proxy, reverse proxy, secure web gateway / SSE / SASE), and content or traffic inspection. Deep specialization in every area is not required, but enough fluency to engage credibly with engineering and with technical customers is.
• Hands-on, regular personal use of AI t