AI Security Engineer

New

Remote in the U.S.Full-TimeMiddle

Salary not disclosed

Apply NowOpens the employer's application page

Job Details

Experience: 3+ years of experience in security engineering with a significant focus on cloud security and/or application security
Required Skills: LLMGenerative AI

Have 3+ years of security engineering experience with a significant focus on cloud security and/or application security.
Bring hands-on experience implementing, managing, securing, and supporting agentic AI solutions in an enterprise context.
Have experience with enterprise AI platforms such as Anthropic Claude, OpenAI ChatGPT Enterprise or Codex, or Microsoft Copilot.
Be familiar with AI-focused cloud services such as AWS Bedrock, AWS SageMaker, Azure AI Foundry, or Google Vertex.
Understand generative AI concepts, large language models, context engineering, agentic tool usage, and foundational AI/ML principles.
Have operational experience using agentic coding assistants such as Claude Code, Open Code, Cursor, or Codex.
Understand AI-specific security challenges including prompt injection, data poisoning, supply chain security, model extraction attacks, excessive agency, and privilege escalation through tool chaining.
Be able to produce professional client-facing assessment reports, findings registers, control matrices, and reference architecture documentation.
Have strong written and verbal communication skills and be able to explain technical concepts to technical and non-technical audiences.
Travel up to 10%.

Conduct secure configuration reviews and security assessments of enterprise AI platforms against established control domains and industry frameworks.
Lead threat modeling for AI workloads, including prompt injection, model inversion, data poisoning, supply chain risks, excessive agency, and privilege escalation through tool chaining.
Assess AI coding tools and development environments for sandbox isolation, plugin allowlisting, secrets access, network egress controls, and CI/CD pipeline security.
Advise client teams on securely integrating SaaS AI services and APIs into enterprise applications.
Evaluate controls for data ingestion pipelines, RAG architectures, and vector databases to prevent unauthorized data exposure and non-compliant processing.
Conduct shadow AI discovery engagements to inventory unsanctioned AI tool usage and assess data exposure risks.
Evaluate AI platform security controls and guardrails, including identity and access management, DLP, conditional access, SIEM and logging, and runtime protections.
Design, build, and deploy AI agent workflows integrated with security tooling and automation platforms.
Perform security architecture reviews for AI agents and deliver reference architectures and recommendations.
Develop engagement deliverables, contribute to client AI security roadmaps, and monitor emerging AI security research and vendor advisories.

View Full Description & ApplyYou'll be redirected to the employer's site