Director, AI Product Management

WatchGuard Technologies

. About the Position . WatchGuard is looking for a Director of AI Product Management to own the strategy and execution for Rai, our agentic, AI-powered action layer built on WatchGuard Cloud, WatchGuard’s MSP focused

Posted 5/29/2026full-timeSeattle • 🇺🇸 United StatesLeadWebsite

Tech Stack

Tools & technologies

CloudCyber Security

About the role

Key responsibilities & impact

About the Position
WatchGuard is looking for a Director of AI Product Management to own the strategy and execution for Rai, our agentic, AI-powered action layer built on WatchGuard Cloud, WatchGuard’s MSP focused security platform. This is a high-impact role at the intersection of agentic AI, cybersecurity, and the managed services market.
Rai handles the MSP workforce jobs that are structured, repeatable, and grounded in data that already lives in WatchGuard Cloud. It doesn’t just surface information; it closes loops. This PM owns what those loops look like, how reliable they are, and how MSPs learn to trust and extend them.
Reporting to the Chief Product Officer, this individual will be responsible for driving the Rai product roadmap, working cross-functionally with engineering, design, channel, and go-to-market teams, and ensuring that WatchGuard’s AI platform delivers measurable value to MSP partners.
A Day in the Life
As a Director of AI on the Platform team, you will work at the center of one of WatchGuard’s most strategically important investments. You will spend your time in direct conversation with MSP partners, understanding how they staff their SOCs and NOCs, where their technicians lose time, and what it would mean to their business to have those hours back. You will translate that understanding into agentic workflows that Rai can own autonomously, and work with engineering to define how those workflows behave when data is incomplete, confidence is low, or actions cannot be undone. AI tools are a native part of how you work; you use them to synthesize customer research, accelerate discovery, apply Spec Driven Design principles to structure requirements before engineering picks them up, and validate prototypes faster than traditional methods allow. You evaluate AI feature quality not just by adoption but by accuracy, reliability, and the degree to which MSPs choose to expand Rai’s scope over time. You drive roadmap alignment across a cross-functional team using working prototypes and real partner feedback, and you partner with PMM and the channel to ensure that what gets built also gets understood and sold.

Requirements

What you’ll need

MSP market knowledge: Deep familiarity with how managed service providers operate, including how they structure their teams, price and deliver services, manage margin pressures, and where technician time goes. You understand that for MSPs, simplicity and automation are not features; they are the business case. You know the difference between a tool an MSP will actually adopt and one that adds process to an already stretched team.
Agentic AI product experience: Demonstrated depth in product management, with meaningful hands-on experience shipping agentic AI or LLM-powered automation in a B2B context — typically 8+ years overall and at least 2 years working directly on autonomous or semi-autonomous AI workflows where the system takes action on behalf of the user. Candidates who have shipped real agentic products recently will be weighted over those with tenure alone.
LLM technical fluency: Hands-on familiarity with how LLMs work in production: context limits, latency tradeoffs, hallucination risks, and when RAG, fine-tuning, or deterministic fallbacks are the right answer.
AI evaluation and governance: Experience defining evaluation criteria and quality standards for AI actions, including how to validate that an automated workflow is safe to run unsupervised.
AI-native product approach: AI tools are part of your core workflow. You use them for customer research synthesis, Spec Driven Design, and prototype validation, getting to a well-structured spec faster and with more rigor than traditional methods allow. You think in terms of what AI can own end-to-end, not just where it can assist.
Product instincts: Strong instincts for what makes an agentic feature genuinely useful versus impressive in a demo, especially in an MSP context where trust, reliability, and low-friction adoption determine whether a product survives the first 90 days.
Cross-functional collaboration: Comfort working across engineering, design, and go-to-market in a fast-moving environment.
Communication skills: Clear, direct communicator who can move between technical depth and business narrative depending on the audience.

Benefits

Comp & perks

Health insurance
401(k) matching
Flexible work hours
Paid time off
Remote work options

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

agentic AILLM-powered automationAI evaluationprototype validationSpec Driven Designautonomous workflowsB2B product managementcustomer research synthesisquality standards for AIdata-driven decision making

Soft Skills

cross-functional collaborationcommunication skillsproduct instinctsclear communicationdirect communicationtrust buildingadaptabilityproblem-solvingstrategic thinkingstakeholder engagement