Staff Product Security Engineer - AI

LinkedIn • Sunnyvale, CA

18h • $152,000 - $248,000 • Hybrid

About The Position

As a Staff Security Engineer on LinkedIn’s Platform & Product Security team, you will strengthen the security posture of LinkedIn’s AI applications, infrastructure, and development workflows. You will research emerging threats, lead threat models, design and implement secure-by-default frameworks, and build scalable tooling to detect and mitigate vulnerabilities across the company. The role is hybrid and based at LinkedIn’s Sunnyvale office, with work performed both from home and in the office on select days as determined by business needs.

LinkedIn’s Information Security organization protects business-critical member data and company assets. The Product Security team proactively safeguards products, applications, and infrastructure by identifying, assessing, and mitigating security and privacy risks. It researches evolving threats and attack vectors, identifies vulnerabilities, provides security consultation, and invests in automation and high-impact security engineering projects.

This role works across platform engineering, security engineering, ML/AI teams, and product/DevEx to drive secure-by-design developer platforms, AI systems, and infrastructure. Compensation is listed at $152,000–$248,000. The total compensation package may also include an annual performance bonus, stock, benefits, and/or other applicable incentive compensation plans.

Requirements

• BA/BS degree in Computer Science, Cybersecurity, Information Security, or a related technical field, or equivalent technical experience.
• Hands-on experience or working knowledge of AI/ML or LLM application security risks, such as prompt injection, data poisoning, and model/provenance integrity.
• At least 5 years of experience in security engineering and in-depth knowledge of application security, authentication and security protocols, cryptography, or supply chain security.
• At least 5 years of experience with security assessment methodologies such as threat modeling, design reviews, penetration testing, and vulnerability assessment.
• Experience with programming languages such as Java, GoLang, or Python.
• Experience architecting or implementing tooling that detects and mitigates security vulnerabilities.

Nice To Haves

• BS and 8+ years of relevant work experience, MS and 7+ years of relevant work experience, or PhD and 4+ years of relevant work experience.
• At least 5 years of experience with programming languages such as Java, GoLang, or Python.
• Experience securing agentic systems, including sandboxing, tool permissioning, and runtime policy enforcement.
• Working knowledge of the modern AI/ML stack, including LLMs and foundation models, RAG architectures, agentic frameworks such as LangChain/LangGraph, CrewAI, or AutoGen, and ML pipelines for training, evaluation, and inference.
• Demonstrated ability to ramp up quickly on AI-specific threats.
• Ability to work across teams and communicate concisely and clearly to stakeholders.
• Experience with security research, bug bounty, or CTF competitions.

Responsibilities

• Lead adoption of security controls across AI/ML infrastructure, including model scanning, model signing and provenance, and ML pipeline security (MLOps/MLSecOps).
• Architect and build security guardrails and paved roads for agentic workflows, including hardened agent SDKs, tool access and permissioning, input/output validation, execution boundaries, sandboxing, and auditability of agent actions.
• Build automation and red-team/detection tooling to continuously identify, reproduce, and mitigate AI-specific vulnerabilities at scale; partner with Detection & Response on prompt/tool-call telemetry and AI-incident playbooks.
• Lead threat modeling and adversarial red-teaming of AI systems, and maintain a LinkedIn AI threat taxonomy mapped to industry standards.
• Partner with security and platform teams to embed threat models and risk assessments into AI platforms, developer tooling, and production services.
• Define AI security standards, reference architectures, and policies across model development, data ingestion, training, inference, and agentic systems.
• Drive secure adoption of AI tooling, including vendors, copilots, and integrations, addressing data-sharing and sensitive-data-in-prompt boundaries.
• Drive cross-functional architecture and engineering decisions across platform engineering, security engineering, ML/AI teams, and product/DevEx to build scalable, reliable, and secure-by-design developer platforms, AI systems, and infrastructure.

Benefits

• Generous health and wellness programs.
• Time away for employees of all levels.
• The total compensation package may include an annual performance bonus, stock, benefits, and/or other applicable incentive compensation plans.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior