Company Description:
Anomali is headquartered in Silicon Valley and is the Leading AI-Powered Security Operations Platform that is modernizing security operations. Anomali delivers the first Intelligence-Native Agentic SOC Platform, unifying a fully-featured-security data lake, threat intelligence, and agentic AI into a single modern experience. Today, we operate in a space where organizations will be left behind if they don’t begin to think and operate differently. Automating important tasks will free up time for operators to do more advanced IT and security work.
Learn more at www.anomali.com
Job Description:
This role requires a strong technical expertise with 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 products.
You will work closely with platform product leadership, 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, strategic product role, combining technical fluency, operational understanding, and strategic vision to help shape the future of autonomous AI in enterprise security.
Key Responsibilities:
- AI-Driven Product Strategy: Collaborate and 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.
Qualifications
Required Skills/Experience:
- 5+ years of Product Management experience with hands-on experience defining innovative AI/ML products or systems.
- Minimum of 3 years in Product Management leadership or advanced, strategic AI driven product innovation
- 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.
- Experience implementing guardrails for AI-driven product 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.
Preferred Qualifications:
- 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.
