Senior Security Engineer, AI Security
USRemotePosted Today$190,800 – $267,100
Full TimeSeniorRemoteUS
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Job Description
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Key Highlights
- Review and threat model AI-powered product features, LLM integrations, agentic workflows, MCP servers, tools, plugins, retrieval systems, model outputs, and internal AI tools before launch.
- Build reusable AI security primitives such as guardrails, scanners, policy checks, tool-use controls, registries, sandboxes, libraries, and workflow-native enforcement points.
- Design security tooling that can sit in the inference, retrieval, or execution path to detect and prevent prompt injection, jailbreaks, tool misuse, data leakage, unsafe code generation, and suspicious agent behavior.
- Partner with teams building products and platforms with AI to define practical security controls that fit how they design, build, and ship.
- Proactively find, fix, and prevent AI security issues, while making any required product or engineering changes clear and low-friction for partner teams.
Qualifications
Required Qualifications
- Experience securing AI/LLM products, AI-assisted development tooling, agent frameworks, MCP-style tool ecosystems, retrieval-augmented generation systems, or model-integrated workflows.
- Experience building guardrails, policy engines, secure frameworks, scanners, linters, CI/CD checks, registries, gateways, or other developer-facing security platforms.
- Familiarity with agent sandboxing, workload identity, network policy, tool permissioning, AI red teaming, or LLM evaluation.
- Experience scanning or governing AI agent components such as skills, prompts, MCP servers, tool manifests, generated code, dependencies, or model-connected workflows.
- Familiarity with machine learning systems, model evaluation, AI data flows, or data governance for AI products.
- Experience with Go, Python, JavaScript, or TypeScript.
- Experience partnering with privacy, trust and safety, infrastructure, platform, or machine learning teams.
- Hands-on experience securing distributed systems or cloud-native applications, including Kubernetes, APIs, and microservices.
- Track record of mentoring engineers or raising the security bar through guidance, tooling, or reusable patterns.
- Experience securing AI/LLM products, AI-assisted development tooling, agent frameworks, MCP-style tool ecosystems, retrieval-augmented generation systems, or model-integrated workflows.
- Experience building guardrails, policy engines, secure frameworks, scanners, linters, CI/CD checks, registries, gateways, or other developer-facing security platforms.
- Familiarity with agent sandboxing, workload identity, network policy, tool permissioning, AI red teaming, or LLM evaluation.
- Experience scanning or governing AI agent components such as skills, prompts, MCP servers, tool manifests, generated code, dependencies, or model-connected workflows.
- Familiarity with machine learning systems, model evaluation, AI data flows, or data governance for AI products.
- Experience with Go, Python, JavaScript, or TypeScript.
- Experience partnering with privacy, trust and safety, infrastructure, platform, or machine learning teams.
- Hands-on experience securing distributed systems or cloud-native applications, including Kubernetes, APIs, and microservices.
- Track record of mentoring engineers or raising the security bar through guidance, tooling, or reusable patterns.
Skills & Technologies
CI/CDMachine LearningGoPythonJavaScriptTypeScriptKubernetes
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Job Details
Employment Type
Full Time
Experience Level
Senior
Salary Range
$190,800 – $267,100
Location
US
Work Mode
Remote
Posted
Today
Country
US