Principal AI Security Engineer
New
Z
ZipAI security
Remote-first opportunity for US-based employees, with the option to work in person from our Manhattan office.Full-TimePrincipal
SalaryThe annual base Pay Range for this position is $203,000-$254,000. This range reflects our US national compensation band (USN). Additional premium percentages may apply based on our tiered premium strategy. The total compensation package for this position may also include other elements, including a bonus and/or commission awards.
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Job Details
- Required Skills
- Python
Requirements
- Demonstrated Staff- or Principal-level technical leadership in security engineering, application security, or cloud security.
- Deep security engineering experience and hands-on work with LLM or agent systems in production, open source, internal platforms, or published research.
- Familiarity with OWASP Top 10 for LLM Applications, MITRE ATLAS, and NIST AI RMF.
- Strong understanding of LLM architectures, agentic systems, RAG, and modern AI development frameworks.
- Experience building AI security evaluations, red-teaming capabilities, or model security gateways, and securing AI systems against prompt injection, data leakage, tool abuse, and unauthorized access.
- Strong software engineering skills, including proficiency in Python or another modern programming language.
- Experience with cloud-native architectures, APIs, containers, IAM, and modern software delivery practices.
- Ability to design and implement security controls, automation, and reusable engineering components.
- Experience threat modeling complex systems and translating security requirements into practical solutions.
- Experience with LangChain, LangGraph, Semantic Kernel, OpenAI APIs, Azure AI, Google Vertex AI, or similar technologies is highly regarded.
- Experience securing MCP servers, autonomous coding agents, or agentic workflows is highly regarded.
- Experience with Microsoft Azure, Google Cloud Platform, Terraform, Kubernetes, and CI/CD security is highly regarded.
Responsibilities
- Define and implement security architecture for LLM applications, RAG systems, autonomous agents, and AI-powered products.
- Engineer protections against prompt injection, data exfiltration, insecure tool execution, excessive agency, and other AI-specific threats.
- Establish secure patterns for model access, non-human identity access, authorization, secrets management, and sensitive data protection.
- Build secure-by-default patterns, harnesses, and guardrails for AI coding assistants, autonomous development agents, and AI-generated software.
- Secure MCP servers, agent tool integrations, and AI-enabled development workflows.
- Build reusable security components, APIs, and automation integrated with engineering platforms and CI/CD pipelines.
- Develop automated security testing, AI red-teaming, prompt-injection testing, and security regression testing.
- Implement monitoring and detection for suspicious AI behavior, unauthorized tool execution, and sensitive data exposure.
- Establish AI security technical direction and engineering standards, and partner with teams to bring secure AI solutions into production.
- Mentor engineers and influence technical decisions across security, platform engineering, and software development.
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