Principle Enterprise Risk Manager

F5 F5 · Enterprise · Seattle, WA

This role is for a Principal Enterprise Risk Manager at F5, focusing on providing strategic risk guidance for various business activities including emerging risks, SaaS, cyber, tech ops, M&A, and product development. The role involves embedding risk considerations into decision-making, using tools like ServiceNow and Jira, analyzing risk data, defining metrics, and advising executive leadership. A key aspect is leveraging AI and machine learning to monitor and predict emerging risk patterns, although this is a preferred skill rather than a core requirement for building AI models.

What you'd actually do

  1. Ensure risk considerations are embedded into high-stakes decision-making processes.
  2. Operate in tools like ServiceNow, Jira, and Aha to streamline risk workflows and reporting processes.
  3. Leverage AI and machine learning to monitor, predict, and proactively address emerging risk patterns and trends.
  4. Analyze and aggregate risk data from across functions to generate actionable insights.
  5. Define metrics and dashboards that give real-time insights into enterprise risk health.

Skills

Required

  • Strong understanding of risk management principles, particularly in the context of M&A activities, strategic partnerships, technology deployments, and market expansions.
  • Expertise in identifying, assessing, and mitigating risks associated with third-party vendor relationships and emerging technologies like SaaS platforms.
  • Proficiency in analyzing and synthesizing risk data from multiple functions to produce actionable insights and strategic guidance.
  • Advanced knowledge and practical experience with risk management tools, such as ServiceNow, Jira, and Aha, for streamlining risk workflows and reporting.
  • Strong collaboration skills, including the ability to work effectively with IT, cybersecurity teams, and senior leadership to align risk management strategies.
  • Advanced analytical and problem-solving skills to aggregate complex risk data and define impactful metrics and dashboards.
  • Exceptional communication and facilitation skills to lead discussions with stakeholders on emerging risks and embed risk considerations into decision-making processes.
  • Strong business acumen and understanding of market, competitive, and macroeconomic factors impacting risk strategies.
  • Proficiency in creating real-time dashboards and metrics to monitor enterprise risk health and performance.
  • Bachelor’s degree in Business Administration, Risk Management, Data Science, or a related field
  • 8-10 years of professional experience in enterprise risk management, data analytics, or a related field, with significant exposure to corporate strategy and operational risk.
  • Experience implementing and managing enterprise tools for workflow and risk reporting.
  • Demonstrated ability to collaborate across technical and operational functions, particularly with IT and cybersecurity teams.
  • Proven track record of successfully defining and delivering metrics, dashboards, and data-driven insights to senior leaders.
  • Strong knowledge of emerging risks in technology, especially SaaS platforms, product innovation, and cybersecurity.
  • Experience advising leadership teams on risk considerations in transformative business contexts such as M&A and market operations.

Nice to have

  • Familiarity with leveraging AI and machine learning for monitoring, predicting, and addressing emerging risks and trends.
  • Practical experience in leveraging AI and machine learning in a risk oversight context is strongly preferred.
  • Certification in risk management or governance are highly desirable.

What the JD emphasized

  • Demonstrable skills in risk and process taxonomies, risk assessment processes, project and stakeholder management are mandatory.
  • Advanced knowledge and practical experience with risk management tools, such as ServiceNow, Jira, and Aha, for streamlining risk workflows and reporting.
  • Practical experience in leveraging AI and machine learning in a risk oversight context is strongly preferred.