Principal Product Manager, Agentic Products at Netskope Cloud Support

Santa Clara, California, United States -

Full Time

Start Date

Immediate

Expiry Date

29 Jun, 26

Salary

260500.0

Posted On

31 Mar, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Product Management, AI Agents, Security Operations, Product Strategy, Roadmap Development, Incident Response, Threat Hunting, Prompt Engineering, UX Design, Data Analysis, LLM Cost Optimization, Cross-functional Influence, Security Workflows, Agent Design, Risk Investigation, Detection Engineering

Industry

Computer and Network Security

Description

About Netskope Today, there's more data and users outside the enterprise than inside, causing the network perimeter as we know it to dissolve. We realized a new perimeter was needed, one that is built in the cloud and follows and protects data wherever it goes, so we started Netskope to redefine Cloud, Network and Data Security. Since 2012, we have built the market-leading cloud security company and an award-winning culture powered by hundreds of employees spread across offices in Santa Clara, St. Louis, Bangalore, London, Paris, Melbourne, Taipei, and Tokyo. Our core values are openness, honesty, and transparency, and we purposely developed our open desk layouts and large meeting spaces to support and promote partnerships, collaboration, and teamwork. From catered lunches and office celebrations to employee recognition events and social professional groups such as the Awesome Women of Netskope (AWON), we strive to keep work fun, supportive and interactive. Visit us at Netskope Careers. Please follow us on LinkedIn and Twitter@Netskope. About the Role Please note, this team is hiring across all levels and candidates are individually assessed and appropriately levelled based upon their skills and experience. We are hiring a Principal Product Manager to lead product strategy for AI-powered agentic security operations at Netskope. This role sits at the intersection of applied AI and security operations where you will own the vision and roadmap for autonomous AI agents that investigate threats, perform security operations tasks, and orchestrate incident response across the Netskope Security Platform. The ideal candidate combines deep security operations domain expertise with genuine fluency in how modern AI agent systems work. Responsibilities Define the product vision and roadmap for agentic security operations, expanding from DLP incident management into risk investigation, threat hunting, policy recommendations, and autonomous response. Gather and prioritize product requirements and user stories. Identify which security workflows are best suited for full autonomy vs. human-in-the-loop agent assistance vs. traditional automation - and draw those boundaries clearly. Own the end-to-end product lifecycle for agentic workflows: from agent design through prompt engineering, investigation quality benchmarking, UX design, launch, and post-launch optimization. Gather and prioritize requirements through direct customer engagement, SOC ride-alongs, field team feedback, and production agent performance data (accuracy, risk score calibration, false positive rates). Collaborate with UX to design the analyst-agent interaction model: how investigations are presented, how analysts provide feedback, how trust is built through transparency into agent reasoning. Collaborate with engineering, design, and marketing teams to deliver successful product launches. Partner with engineering to evaluate and improve agent investigation quality - running evals to improve the accuracy, reliability, and safety of agents, tuning investigation workflows, and defining quality benchmarks for risk assessments, recommended actions, and incident summaries. Define success metrics for agent performance: accuracy, risk score precision, time-to-resolution improvements, and cost-per-investigation. Act as the primary product voice for agentic security operations across the organization - translating complex AI/agent capabilities into customer value for sales, marketing, and executive stakeholders. Partner with agentic platform engineering on agent infrastructure: LLM cost optimization, latency budgets, multi-tenant isolation, and scaling agent workloads across management planes. Present product updates and strategies to stakeholders. Monitor product performance and make data-driven decisions for improvement. Qualifications Mandatory: 10+ years of work experience in the Software/IT industry is mandatory. 7+ years of Product Management experience is mandatory. Demonstrated understanding of SOC workflows: alert triage, incident investigation, threat hunting, detection engineering, and incident response. You should be able to describe what an L1 analyst does differently from an L3 threat hunter. Working knowledge of modern AI/ML agent architectures - you don't need to write code, but you should understand concepts like multi-step agent workflows, tool use, prompt engineering, RAG, and the tradeoffs between autonomous and human-in-the-loop agent designs. Hands-on product instincts - you do UAT, run live demos, review investigation outputs, challenge prompt designs, and write detailed acceptance criteria. Experience representing the customer: building relationships with security practitioners, running SOC ride-alongs, and translating analyst pain into product requirements. Track record of shipping products in fast-paced environments with overlapping workstreams and ambiguity. Desirable: 5+ years of experience building or product managing cyber-security products is desirable. Experience building AI-powered products that went to production - not prototypes or demos. You've dealt with LLM hallucination, cost management, latency constraints, and quality measurement at scale. Familiarity with the MITRE ATT&CK framework, common detection rule formats, and how SOC teams operationalize threat intelligence. Experience with security data pipelines: event ingestion, alert correlation, enrichment, and the data challenges of multi-tenant security platforms. Previous experience in a technical role (security engineering, detection engineering, solution architecture, or SOC analyst) before moving into product management. Skills Analytical rigor: You define success metrics before building, measure agent quality empirically, and make decisions with data. You can read a confusion matrix and explain why precision matters more than recall for autonomous remediation actions. Technical communication: You can whiteboard an agent workflow architecture with engineering, explain risk scoring methodology to a CISO, and write a crisp PRD that an L1 analyst would validate as accurate to their daily workflow. Security domain depth: You think in terms of attack paths, blast radius, lateral movement, and dwell time - not just features and user stories. AI product judgment: You have good instincts for when an LLM will perform well vs. poorly, when to use deterministic logic vs. AI reasoning, and how to design graceful fallbacks when agent confidence is low. Cross-functional influence: You lead through clarity and conviction, not authority. You can align engineering, design, sales, and executive stakeholders around a shared vision. Self-directed execution: You thrive in ambiguity, break down complex problems, and ship iteratively without waiting for perfect information. Education & Travel BS/BA in Computer Science, Cybersecurity, or related technical field required. MS or MBA preferred. Ability to travel up to 25% (domestic and international for customer visits, SOC ride-alongs, and industry events). Benefits Competitive salary and benefits package. Opportunity to define a new category at the intersection of AI agents and security operations - this is not incremental feature work. Direct impact on how security teams worldwide detect and respond to threats. Collaborative, engineering-driven culture where PMs are expected to go deep on technology. #LI-SC1 Compensation: At Netskope, salary is one component of our competitive total rewards package. The salary range for this position is as listed below. This is a national range. For purposes of complying with applicable laws, the range applies to candidates in California, Colorado, Illinois, Maryland, New York, Washington, and other states. The successful candidate’s starting pay will also be determined based on job-related skills, experience, qualifications, location, and market conditions. For all sales roles, the posted salary range is the On Target Earnings (OTE) range for the role, which is the sum of base salary and target commission amount at 100% goal achievement. In addition to salary, candidates may be eligible for other forms of compensation such as participation in a bonus plan (for non-sales roles) and a stock award program. Candidates may also be eligible for a comprehensive health plan and other benefits that can be reviewed at Netskope Benefits site. Salary Range $128,000—$260,500 USD Netskope is committed to implementing equal employment opportunities for all employees and applicants for employment. Netskope does not discriminate in employment opportunities or practices based on religion, race, color, sex, marital or veteran statues, age, national origin, ancestry, physical or mental disability, medical condition, sexual orientation, gender identity/expression, genetic information, pregnancy (including childbirth, lactation and related medical conditions), or any other characteristic protected by the laws or regulations of any jurisdiction in which we operate. Netskope respects your privacy and is committed to protecting the personal information you share with us, please refer to Netskope's Privacy Policy for more details. The application window for this position is expected to close within 50 days. You may apply by filling out the below information, or visiting our Netskope Careers site.

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Responsibilities

The Principal Product Manager will define the product vision and roadmap for AI-powered agentic security operations, expanding from incident management into threat hunting and autonomous response. This involves owning the end-to-end product lifecycle, from agent design and prompt engineering through to launch and post-launch optimization based on rigorous performance benchmarking.