Senior Security Engineer, AI Security
New
R
RedditTechnology
Remote - United StatesFull-TimeSenior
Salary$190,800 — $267,100 USD
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Job Details
- Experience
- 5+ years of experience
- Required Skills
- PythonJavascriptKubernetesTypeScriptGoLLM
Requirements
- 5+ years of experience in product security, application security, software security, security engineering, backend engineering, or security platform engineering.
- Strong application security fundamentals, including secure design review, threat modeling, code review, vulnerability prioritization, and practical remediation.
- Experience in building reliable backend services.
- Hands-on experience building security automation, developer tooling, libraries, infrastructure, or platform controls.
- Familiarity with AI, LLM, or agentic system risks such as prompt injection, jailbreaks, insecure tool use, tool poisoning, data leakage, unsafe model outputs, and abuse of AI-assisted workflows.
- Ability to reason across trust boundaries, including user input, model context, retrieval systems, backend services, tool calls, MCP servers, third-party integrations, sandboxed execution, logs, and frontend rendering.
- Practical understanding of infrastructure security concepts such as identity, authorization, network boundaries, secrets, cloud environments, containers, isolation, runtime policy enforcement, and least privilege.
- Strong engineering judgment about when to block launch, when to accept risk, and how to sequence practical remediations.
- Clear communication skills with the ability to explain technical security risk and business impact to engineers, product managers, and leadership.
Responsibilities
- 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.
- Turn one-off AI security issues into systemic fixes, paved paths, measurable controls, and reusable guidance.
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