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AI Product Manager

Roles & Responsibilities

  • Bachelor's degree or higher in a technical field (or equivalent experience)
  • 5+ years of experience in software engineering, product development, or a hybrid role, including building AI-powered applications
  • Strong hands-on experience with LLMs and AI coding tools for prototyping, analysis, and product development
  • Experience building systems that incorporate GenAI (e.g., LLM integrations, RAG pipelines, agentic workflows, evaluation frameworks)

Requirements:

  • Rapidly prototype and ship new security features using AI coding tools and modern development workflows to explore product ideas and technical feasibility
  • Leverage internal data, threat intelligence, and market signals to identify high-impact opportunities and validate product direction
  • Own product definition end-to-end—translating ambiguous problems into clear requirements and shipped solutions across cloud platforms, APIs, and security infrastructure using GenAI
  • Collaborate cross-functionally with engineering, security researchers, and business stakeholders to deliver impactful outcomes and automate workflows with agentic AI systems

Job description

7AI is seeking an AI-Native Product Builder to design and launch intelligent security products that help organizations proactively defend against evolving cyber threats. This role blends product thinking with hands-on engineering, enabling you to move from idea to production quickly using AI-first workflows.

You’ll work at the intersection of cybersecurity, AI, and product innovation—building systems that detect, analyze, and respond to threats in real time. From early concept validation to production deployment, you’ll own the full lifecycle of new capabilities, collaborating closely with engineering, research, and go-to-market teams.

The ideal candidate is deeply technical, AI-native in how they build, and energized by solving complex security problems in a fast-moving, high-ownership environment.

What You’ll Do

  • Rapidly prototype and ship new security features using AI coding tools (e.g., Cursor, Copilot) and modern development workflows to explore product ideas and technical feasibility.

  • Leverage internal data, threat intelligence, and market signals to identify high-impact opportunities and validate product direction.

  • Build and scale features across cloud platforms, APIs, and security infrastructure using GenAI to accelerate development while maintaining high standards for reliability and security.

  • Own product definition end-to-end—translating ambiguous problems into clear requirements and shipped solutions.

  • Balance trade-offs across security effectiveness, performance, usability, and operational complexity.

  • Partner cross-functionally with engineering, security researchers, and business stakeholders to deliver impactful outcomes.

  • Identify opportunities to automate workflows across teams using agentic AI systems and internal tooling.

  • Contribute to the evolution of next-generation AI-driven cybersecurity capabilities, including detection, response, and analysis systems.

What We’re Looking For

  • Bachelor’s degree or higher in a technical field (or equivalent experience).

  • 5+ years of experience in software engineering, product development, or a hybrid role, including building AI-powered applications.

  • Strong hands-on experience with LLMs and AI coding tools for prototyping, analysis, and product development.

  • Experience building systems that incorporate GenAI (e.g., LLM integrations, RAG pipelines, agentic workflows, evaluation frameworks).

  • Proven ability to take products from concept to launch with a strong focus on user impact.

Nice to Have

  • Experience building security or infrastructure products (e.g., detection systems, monitoring tools, or distributed services).

  • A portfolio of projects demonstrating AI-native development and rapid prototyping.

  • Experience instrumenting products with analytics and telemetry to drive decision-making.

  • Familiarity with cloud infrastructure (e.g., AWS) and data visualization tools.

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