Remote Product Security Engineer for AI Systems

• Architect and build AI-powered security systems that autonomously identify, triage, and remediate vulnerabilities across applications, infrastructure, and AI workloads.
• Develop agentic security workflows leveraging LLMs and machine learning for code review, threat detection, vulnerability correlation, root-cause analysis, and automated fix generation.
• Reimagine the Secure Software Development Lifecycle (SSDLC) by integrating intelligent security controls, AI guardrails, and continuous validation into CI/CD pipelines.
• Lead threat modeling initiatives for distributed systems, AI platforms, RAG architectures, model-serving infrastructure, data pipelines, and autonomous agents.
• Design security frameworks to protect AI systems against emerging threats including prompt injection, model abuse, data poisoning, adversarial attacks, and sensitive data leakage.
• Build behavioral detection models and risk engines to identify synthetic identities, document fraud, account takeover attempts, and other adversarial activity within customer onboarding and KYC workflows.
• Apply machine learning and contextual risk scoring to reduce alert fatigue, prioritize security findings, and drive autonomous remediation decisions.
• Partner closely with engineering, platform, and AI research teams to ensure security is embedded as a native capability rather than a downstream function.
• Scale a culture of security engineering through mentorship, technical leadership, and enablement programs focused on secure AI development practices.

• Demonstrated experience building or applying AI/LLM-powered security solutions, including agentic workflows, autonomous remediation systems, vulnerability discovery, or security copilots.
• Deep expertise in Application Security, Product Security, or Security Engineering with a strong software development background.
• Hands-on experience integrating enterprise security tooling (e.g., Snyk, Checkmarx, GitHub Advanced Security, Semgrep, Wiz, Lacework) into automated developer workflows and AI-driven orchestration platforms.
• Strong understanding of modern security architecture, cloud-native systems, APIs, microservices, and distributed computing environments.
• Deep familiarity with OWASP Top 10, OWASP Top 10 for LLM Applications, secure AI development practices, and emerging AI threat models.
• Advanced programming skills in Python and at least one additional language such as Go, Java, Rust, or Node.js.
• 8+ years of experience in relevant fields., Are you experienced in managing Windows and Linux systems with a passion for building highly-available infrastructure at massive scale? Join us in driving cloud innovation and auto…

Full-time position with remote work flexibility. Compensation

Annual salary range of $250, 000 - $400, 000. Eligibility

The role of a Product Security Engineer is pivotal in shaping the future of AI-native security engineering. This position operates at the intersection of application security, machine learning, and developer productivity, focusing on the design of autonomous security systems that scale with modern software development practices. You will lead the evolution of our security platform by embedding AI-driven controls directly into the software lifecycle, enabling continuous risk discovery, intelligent remediation, and secure deployment at the speed of innovation., SaidGig

• Seattle, WA

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