Principal Cybersecurity Engineer

Responsibilities

• Architect the development of our internal Cybersecurity Risk Management and Automation tools.
• Serve as the primary visionary for how risk data is structured, analyzed, and automated, acting as the bridge between the Cybersecurity Risk organization and Engineering teams.
• Translate risk philosophy into the logic used by engineering squads; own the translation of strategic risk concepts into technical specifications.

• Basic Qualifications
• 9+ years of experience building custom GRC (Governance, Risk, and Compliance) platforms.
• Software Engineering & Development:
  Proficiency in Python, Go, or Java with strong Git/version control, API design, and ability to build complex PoCs for risk models.
• Full-Lifecycle Engineering Governance:
  End-to-end SDLC experience, including creation and oversight of SRS documentation, Project Plans, and Product Backlogs to ensure architectural alignment from planning through deployment and maintenance.
• Architectural & Quality Standards:
  Ability to define system architectures, data models (ERDs), and API specifications, with QA through formalized Test Plans, automated Build Scripts, and Production Operations manuals.
• Experience leading the technical roadmap for software engineering teams or data scientists without direct reporting authority (e.g., Lead, Principal, or Staff level).
• Technical Influence:
  Data & Automation Engineering:
  Proficiency in data pipeline logic, ELT/ETL, and data quality assurance for automating security telemetry.
• Other Qualifications
• Strategic Technical Translation:
  Architect high-level business and security end-states into sophisticated process designs and technical specifications; translate risk philosophy into engineering logic.
• Risk Domain Authority: SME for defining risk metrics and calculation methodologies, within enterprise risk (ERM) and third-party risk (TPRM).
• Cross-Functional Influence:
  Champion security risk automation, mentor junior engineers, and influence stakeholders on data-driven risk modeling practices.

• Essential Domain Knowledge
• Mastery of Cybersecurity Risk:
  Experience designing and implementing Enterprise and Third-Party Risk Management programs at scale.
• Architectural Design:
  Ability to define complex security processes and translate them into technical user stories and functional specifications.
• Advanced Risk Modeling:
  Expertise in quantitative risk analysis (e.g., Monte Carlo simulations or FAIR) and applying models to software.