Director of Product Management, Platform & AI

About Gurucul

-----------------

As the threat of autonomous attacks and rogue agents grows, security teams are rushing to adapt. Right now they are deciding how much work to hand to AI, and what it takes to trust an AI’s conclusion before it acts. Gurucul has spent more than a decade on the groundwork for that trust: learning how users, systems, and now AI agents normally behave, and showing the evidence when behavior changes.

We were early to market with an AI SOC solution that supports analysts at every stage of the lifecycle. We helped pioneer user and entity behavior analytics (UEBA), and we’re a Leader in the 2025 Gartner® Magic Quadrant™ for SIEM. This is all unified by a platform that connects SIEM, Insider Risk Management, and AI Risk and Response, with AI agents embedded into the workflows.

Role Summary

----------------

You’ll own the AI platform under every Gurucul product: the models, agents, and evidence that SIEM, Insider Risk Management, and AI Risk and Response build on, and every way people and other systems reach them. Some customers will work in their own AI Consoles. Others will want Gurucul’s detections, investigations, and actions inside the AI tools and workflows they already run, through APIs and MCP.

You’ll decide where we invest and take this through execution and deployment, working closely with our customers. This is the biggest area for innovation in security and you’ll be at the center of it. You’ll work closely with colleagues across multiple time zones, requiring flexibility in working hours and comfort operating in a distributed organization.

In this role, you’ll be both a hands-on product leader and an organizational leader, initially driving the platform directly and, over time, managing and coaching product managers and product owners. You’ll report to our VP of Product Management and work across Engineering, Research, UX, and the product teams.

This role suits someone who has led a platform through a major change in how customers used it, and who can make hard calls before the market settles. Those calls will shape Gurucul for years, and you’ll explain them to customers, analysts, and industry audiences.

Key Responsibilities:

-------------------------

Platform strategy and business ownership

• Set AI platform strategy across SIEM, Insider Risk Management, and AI Risk and Response. Decide which capabilities belong in the shared platform and which belong to one product, and make investment calls on customer value, differentiation, effort, and risk.
• Define how Behavioral AI, deterministic detections, Unified Entity Intelligence, LLMs, and agents work together. Set priorities for prediction and prevention, and be explicit about what the platform can infer, what it can stop, and when a person must approve the action.
• Own the business case. Work with Product Marketing, Sales, and Finance on positioning, pricing, packaging, and launches, including how to price AI capabilities used through APIs and agents. Track adoption, customer outcomes, revenue contribution, and the cost of running AI features.

Interfaces and ecosystem

• Own the AI Console with UX and Engineering: how people ask questions, inspect evidence, direct agents, approve actions, and recover from mistakes. Measure whether people finish the work with less effort.
• Set direction for APIs and Model Context Protocol (MCP) integrations, covering both Gurucul agents that call external tools and external AI systems that call Gurucul. Define use cases, permissions, tenant boundaries, approval rules, and audit trails so a capability behaves the same however it’s invoked. Decide where to partner with model providers and AI platforms and where to build.

Trustworthy AI and discovery

• Make grounding and guardrails product requirements: evidence behind every conclusion, access controls, data privacy, tool permissions, human approval, audit trails, and safe failure handling. Work with Engineering and Research on prompt injection, data leakage, and unintended actions.
• Set evaluation standards with Research and Engineering before release and monitor performance after. Track task completion, evidence quality, wrong conclusions or actions, analyst overrides, latency, and cost. Require regression checks as models, prompts, and tools change, and stop capabilities that don’t hold up.
• Lead discovery with SOC and insider risk practitioners and design partners. Use prototypes and pilots to test usefulness, feasibility, willingness to pay, and whether customers trust the results enough to rely on them, before committing major investment.

Leadership and influence

• Hire, manage, and coach product managers. Lead initiatives across teams outside your reporting line: get agreement on priorities, owners, and success measures, raise risks early, and settle disagreements with evidence. Engineering owns architecture and implementation; you own the problem, the priorities, and the acceptance criteria.
• Represent Gurucul with customers, analysts, and conference audiences. Demo the platform, explain where our AI is headed and what it can’t do yet, and work with Product Marketing on a story the product can back up.

Required Qualifications

---------------------------

• 10+ years of product management or product leadership in enterprise software, including ownership of strategy and delivery across multiple teams and experience managing product managers.
• Experience operating in a fast-growing environment with startup-like constraints, balancing strategic investments, customer commitments, and engineering capacity.
• You’ve shipped AI products into production, including LLM or agent capabilities. You understand retrieval and grounding, tool use, evaluation, model selection, and the tradeoffs among quality, latency, and cost.
• You’ve owned a platform or API product that other teams, partners, or customers built on. You’re fluent in integrations, data platforms, and enterprise SaaS, and can write requirements for MCP-based integrations and work through tradeoffs with Engineering.
• You know security operations well enough to see what a wrong AI conclusion or action costs, and you can work with specialists on detection, investigation, and response.
• You’ve used research, prototypes, and pilots to change a roadmap, and you can tie product decisions to adoption, customer outcomes, pricing, or revenue.
• You communicate clearly with practitioners, engineers, executives, and public audiences, and you’ve won support for a direction before it was obvious.

Preferred Qualifications (Nice-to-Have)

---------------------------------------------

• Experience building security agents, predictive analytics, or prevention and response capabilities with customer-defined controls.
• Experience with MCP servers, agent orchestration, or AI consoles, including production evaluation and enterprise access controls.
• Experience combining behavioral models, deterministic logic, knowledge graphs, and generative AI in one product.
• Experience leading platform products at a growing enterprise software company.

Compensation & Benefits

----------------------------

• Annual base salary range: $180,000 – $210,000
• Gurucul offers a competitive compensation package, including medical, dental, vision, and life insurance, EAP, 401K, Paid Time Off, and paid Holidays

Location

------------

• Hybrid in El Segundo, CA, or remote within the US.

Equal Opportunity

Employer ------------------------------

Gurucul Solutions, LLC is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

To apply ------------

Please send resumes to [email protected] for consideration.