Senior Security Engineer, AI Security

EngineersOfAI; United States; On-site; USD 120,000 - 160,000; Full time

Job summary

EngineersOfAI is seeking a Senior Security Engineer, AI Security to enhance the security of AI-powered products. This role involves reviewing AI designs, threat modeling, and building security tools for various applications within the company.

The ideal candidate will have over 5 years of experience in product and application security, alongside strong problem-solving instincts. You'll be expected to proactively find and fix AI security issues, ensuring smooth collaboration with engineering teams.

Qualifications

• 5+ years in security engineering, application security, or related field.
• Strong fundamentals in secure design review, threat modeling, and code review.
• Hands-on experience in building security automation and tooling.

Responsibilities

• Review and threat model AI product features and integrations.
• Design security tooling for detection and prevention of vulnerabilities.
• Find and fix AI security issues proactively.

Skills

Product security judgment

Application security fundamentals

Experience in AI security risks

Vulnerability prioritization

Building reliable backend services

Security automation

Threat modeling

Job description

Reddit is a community of communities. It is built on shared interests, passion, and trust and is home to some of the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about.

About The Role

Reddit is hiring a Senior Security Engineer, AI Security to help teams build and ship AI‑powered products securely. This role combines product security judgment with hands‑on engineering to secure the systems, tools, and workflows behind Reddit's AI efforts.

You will review AI-powered product designs, threat model LLM and agentic workflows, and build reusable security primitives that make secure AI development easier for teams across Reddit. This is not an MLE role, but you should be comfortable reasoning about how AI systems fail, how agents use tools, and how security controls fit into inference, retrieval, tool‑use, and execution paths.

The best candidates combine practical application security judgment with strong builder instincts. They can identify risks before launch, then turn repeated findings into guardrails, scanners, registries, sandboxes, libraries, policy checks, or platform controls that scale beyond one product team.

What You'll Do

• 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.

What We're Looking For

• 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 understandin