Senior Product Manager, AI-Driven Security Operations

Company

Description:

Anomali is headquartered in Silicon Valley and is the Leading AI-Powered Security Operations Platform that is modernizing security operations. At the center of it is an omnipresent, intelligent, and multilingual Anomali Copilot that automates key workflows and empowers your team to deliver critical threat insights to leadership in seconds.

Anomali unifies ETL, SIEM, XDR, SOAR, and the world’s largest repository of global intelligence into a single, cloud-native platform that improves detection, speeds investigations, and reduces costs at scale.

Do more with less. Be Different.
Be the Anomali.

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This role requires a strong technical understanding of AI/ML systems
, including LLMs, retrieval-augmented reasoning, multi-agent orchestration, prompt engineering, reinforcement learning, and model evaluation, and the ability to translate these capabilities into production-ready, reliable, and safe AI-driven features for security operations.

You will work closely with Engineering, Data Science, and Security Research teams to define technical requirements, prioritize features, and guide the development of an autonomous SOC+ product that automates threat detection, triage, response, and analyst decision support at scale.

This is a hands-on, high-impact product role
, combining technical fluency, operational understanding, and strategic vision to shape the future of autonomous AI in enterprise security.

• AI-Driven Product Strategy: Define the vision, roadmap, and success metrics for autonomous SOC+ features, ensuring alignment between AI capabilities, SOC workflows, and customer needs.
• Technical Requirements & Architecture Input: Translate AI research into scalable, production-grade features, including agentic AI workflows, automated triage, alert prioritization, threat detection, and multi-agent orchestration.
• Model Evaluation & Reliability: Partner with evaluation and reliability teams to define SLIs/SLOs, performance KPIs, and operational guardrails for autonomous AI systems.
• Workflow Translation: Map SOC analyst and incident response workflows to AI automation opportunities while ensuring usability, explainability, traceability, and auditability.
• Cross-Functional Leadership: Collaborate with Product, Engineering, Security Research, UX, and GTM teams to drive feature prioritization, validate technical feasibility, and ensure production readiness.
• Thought Leadership & Industry Presence: Represent the product internally and externally through executive briefings, panels, webinars, and whitepapers to highlight AI-driven SOC automation.

• 5+ years of Product Management experience with hands-on experience defining AI/ML products or systems.
• Strong technical understanding of LLMs, multi-agent systems, retrieval-augmented reasoning, prompt engineering, reinforcement learning, and evaluation frameworks.
• Proven experience translating complex AI capabilities into production-ready features.
• Deep understanding of SOC workflows, incident response, and enterprise security operations.
• Proven ability to define success metrics, evaluate model performance, and monitor reliability of AI systems in production.
• Excellent communication skills to bridge technical, product, and security teams.
• This position is not eligible for employment visa sponsorship. The successful candidate must not now, or in the future, require visa sponsorship to work in the US.
• For candidates in the Bay area, this position is onsite/hybrid at our Redwood City, CA office. Currently, the team is working a hybrid schedule:
  Mon/Tue/Wed onsite and Thu/Fri remote. We will also consider remote candidates located within the Unites States.

• Experience with production AI systems: multi-agent orchestration, tool-using agents, autonomous workflows, or real-time ML/AI pipelines.
• Familiarity with AI safety, adversarial testing, explainability, and auditability frameworks.
• Experience delivering AI-driven products in high-growth, startup, or fast-moving enterprise environments.
• Advanced degree in Computer Science, Machine Learning, AI, or a related field.