Security Data & AI Engineer: Predictive Risk & Automation

What you'll be doing...

Verizon's Exposure and Vulnerability Management (EVM) team is seeking a Data & AI Engineer to lead the development, implementation, and intelligent automation of our security data system. In this role, you will be the hands‑on driving force building scalable data pipelines, creating data dashboards, reports and developing AI models to predict, prioritize, cybersecurity vulnerabilities.

While your primary focus will be engineering robust data and AI Reporting systems, strong architectural capabilities are a major plus. You will have the opportunity to influence the blueprint of how diverse asset data is structured and meaningfully delivered.

By engineering data models and AI pipelines, the role will help ensure our infrastructure is ready for predictive analytics and that our reporting solutions provide proactive, AI‑driven insights rather than just historical data.

• Data Modeling & Architecture:
  Designing and implementing comprehensive data models (conceptual, logical, physical) that normalize and dimensionalize complex security data across numerous sources, optimized for both BI and AI workloads.
• System Integration & Hub Strategy:
  Onboarding of new data sources and Systems of Record (SoR) into the Cyber Data Hub, ensuring data is clean, transformed, labeled, and optimized for LLM/ML consumption.
• Framework Development:
  Creating reusable, automated frameworks and MLOps workflows for data processing to ensure low-touch reporting as well as building sustainable AI-driven insights.
• Analytics & Data Science Partnership:
  Collaborating with the Analytics-as-a-Service and Data Science teams to engineer the underlying data structures that enable self-service BI and seamless predictive model training.
• Data Integrity & Governance:
  Implementing strict data quality checks, compliance safeguards, and bias-mitigation code to ensure the absolute integrity of AI inputs and EVM reporting.
• Technical Leadership:
  Translating complex security program needs into concrete engineering tasks, guiding junior engineers and serving as a key technical liaison between security operations and core engineering.
• Maintaining our Testing and UAT reporting environments.

You are a builder with a vision‑someone who views data through the lens of security risk and creating ways to automate complex problems. You should be deeply analytical, thrilled by optimizing massive datasets, and eager to leverage AI to stay ahead of emerging threats. You flourish in fast‑paced environments and possess the technical credibility to guide both engineering execution and architectural direction.

• Bachelor's degree or four or more years of work experience.
• Eight or more years of relevant experience required, demonstrated through one or a combination of work and/or military experience, or specialized training.
• Five or more years of relevant work experience in data engineering, AI/ML infrastructure, or data architecture.
• Experience designing high‑level data blueprints, system topology, and enterprise‑wide data strategies.
• Experience scripting with Python (including libraries like Pandas, Num Py) and SQL for complex data manipulation and engineering.

• Advanced experience in writing, optimizing, and debugging complex queries and schemas for relational (SQL Server, Oracle, MySQL) and non‑relational databases.
• Proven experience building enterprise‑grade production pipelines using modern data orchestration tools (e.g., Airflow, Prefect, or cloud‑native tools).
• Experience optimizing data layers for BI tools (Looker, Tableau, Power BI) and integrating pipelines with modern AI platforms.
• Prior experience engineering within a Vulnerability Management program or Cyber Security organization.
• Exceptional ability to translate client needs into achievable technical requirements and present AI/data roadmaps to executive leadership.
• Hands‑on experience fine‑tuning Large Language Models (LLMs), building Retrieval‑Augmented Generation (RAG) frameworks for security logs, or developing predictive risk‑scoring algorithms.
• Understanding of security frameworks (NIST, SOX, FISMA)…