Principal AI Security Developer

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As a Principal AI Security Developer, you will be the driving force behind the next generation of Verizon's AI-driven defensive capabilities. We are looking for a deep-tech security practitioner who specializes in building and securing the AI systems that protect our infrastructure. You will partner directly with Cyber leadership to ideate and deliver high-concurrency, AI-powered applications that automate compliance flows, security operations processes, and other critical areas of our Cybersecurity organization. You aren't just writing code; you are engineering the future of Cyber AI Assurance, ensuring our AI workflows are resilient against prompt injection, data poisoning, and model inversion. If you are a security expert who views AI as your primary tool for scale and defense, this is your role.

Roles and Responsibilities:

• Business Translation & Proactive Ideation: Consulting directly with Cyber business leaders to deeply understand operational challenges and proactively ideating, designing, and translating high-level business needs into defined, technical requirements and actionable, high-value AI-powered applications.

• Cyber AI Assurance & Security: Ensuring developed AI/ML systems and agentic workflows adhere to Verizon Cybersecurity standards, including secure coding practices, vulnerability management, and the implementation of AI-specific security controls (e.g., addressing prompt injection, data poisoning, and model inversion risks).

• Full Stack Tooling & Visualization: Building high-concurrency APIs using FastAPI and developing front end solutions to support ML-based anomaly detections.

• Automation with GenAI: Designing and deploying AI agents using LangGraph or CrewAI to automate critical Verizon Cybersecurity functions, including incident triage, reputation lookups, evidence evaluation, and report generation.

• Engineering for Data Science: Architecting and maintaining robust data pipelines to support data scientists working on anomaly detection and threat hunting models.

• Big Data Processing: Managing large-scale log ingestion and processing capabilities within GCP (utilizing Dataflow and Dataproc) and AWS containerized environments.

• Infrastructure & Deployment: Deploying applications to containerized environments (Docker/Kubernetes/GKE), managing CI/CD pipelines to ensure reliability, and supporting model deployment evaluation via VertexAI and MLOps practices.

• Observability & Reliability: Implementing deep instrumentation using OpenTelemetry (OTel) for instrumenting Python applications and manual instrumentation of complex workflows (Spark, AI Agents), while creating Grafana dashboards to visualize metrics, distributed traces, and logs.

• Bachelor's degree or four or more years of work experience.

• Six or more years of relevant work experience required, demonstrated through one or a combination of job-related work experience, military experience, or specialized training or education (non-collegiate).

• Background in Cybersecurity or Anomaly Detection.

• Experience in Python and/or JavaScript; proven experience working within Agile methodologies.

• Experience building AI systems and/or multi-agent workflows and/or RAG implementations using frameworks like LangChain, LangGraph, or CrewAI, integrated with Vector Databases (e.g., pgvector) within the VertexAI environment or a similar technology.

• Backend experience in FastAPI (asynchronous REST APIs) and/or Flask (microservices) combined with experience managing middleware gateways such as Kong, Apigee, or ApiSix or similar technology.

• Experience with Cloud Service providers (GCP, AWS, etc.) deploying and managing resources therein to include containers, compute instances, logging, etc.

• Data Engineering & Big Data: Knowledge of Python data science libraries (Pandas, NumPy, Scikit-learn).

• LLM Production & Security: Demonstrated success integrating LLMs into production workflows, including MCP implementations, security best practices, and OAuth/OIDC authentication standards.

• Strong background in developing automated testing suites and managing end-to-end deployment pipelines.

• Experience interacting with SIEM APIs (Splunk, Chronicle, Elastic).

• Frontend proven ability with Plotly Dash for complex data visualisation.

• Experience with GKE Looker.

• Proficiency in Apache PySpark for writing, optimising, and tuning Spark jobs for large datasets.

• Experience building complex DAGs using orchestration tools like Apache Airflow or Dagster.

• Hands-on experience with GCP Data Services, specifically Google Cloud Dataflow (Apache Beam) and Cloud Dataproc.

• Proficiency with SQL (BigQuery), Kafka, Parquet format, and handling both batch and streaming paradigms.

• Observability: Experience with OpenTelemetry (OTel). Expertise in Grafana for visualisation. Familiarity with metrics backends such as Prometheus, Google Cloud Monitoring, or similar time-series databases.

If Verizon and this role sound like a fit for you, we encourage you to apply even if you don't meet every "even better" qualification listed above.

Verizon is an equal opportunity employer. We evaluate qualified applicants without regard to veteran status, disability or other legally protected characteristics.

Our benefits are designed to help you move forward in your career, and in areas of your life outside of Verizon. From health and wellness benefit options including: medical, dental, vision, short and long term disability, basic life insurance, supplemental life insurance, AD&D insurance, identity theft protection, pet insurance and group home & auto insurance. We also offer a matched 401(k) savings plan, up to 8 company paid holidays per year and up to 6 personal days per year, paid parental leave, adoption assistance and tuition assistance, plus other incentives, we've got you covered with our award-winning total rewards package. Depending on the role, employees have the opportunity to receive compensation in the form of premium pay such as overtime, shift differential, holiday pay, allowances, etc. Newly hired employees receive up to 15 days of vacation per year, which grows with additional service. For part-timers, your coverage will vary as you may be eligible for some of these benefits depending on your individual circumstances.