Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 3
API @ 4
CI/CD @ 4
Communication @ 6
Distributed Systems @ 4
Go @ 4
JavaScript @ 4
Kubernetes @ 4
LLM @ 3
Leadership @ 6
Machine Learning @ 3
Mentoring @ 6
Microservices @ 4
Prioritization @ 7
Python @ 4
RAG
Security @ 6
TypeScript @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
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.
The role involves reviewing AI-powered product designs, threat modeling LLM and agentic workflows, and building reusable security primitives that make secure AI development easier across Reddit. This is not an MLE role, but the successful candidate 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.
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 for inference, retrieval, and execution paths to detect and prevent prompt injection, jailbreaks, tool misuse, data leakage, unsafe code generation, and suspicious agent behavior.
- Partner with product and platform teams to define practical security controls that fit their development and delivery processes.
- Proactively find, fix, and prevent AI security issues while making 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.
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 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, including 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 involving 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 and the ability to explain technical security risks and business impact to engineers, product managers, and leadership.
Preferred 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.
Benefits
- Equity in the form of restricted stock units.
- Potential commission eligibility depending on the position offered.
- Medical, dental, and vision insurance for U.S.-based employees.
- 401(k) program with employer match.
- Generous vacation time and parental leave.
- Reddit is an equal opportunity employer and provides reasonable accommodations for qualified individuals with disabilities and disabled veterans.
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