Ripple

1 month ago

Senior Staff Security Engineer, AI

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 hour agoStatus: Live

Job Summary

Own AI security at Ripple, serving as a deep technical expert across the agentic SDLC. Lead the AI security strategy and roadmap, define and operationalize LLM and agentic guardrails, and implement controls such as sandboxing, identity/permissions scoping, runtime monitoring, and audit trails. Drive security reviews for AI integrations entering production and build Shadow AI detection to enforce acceptable use—while shaping Ripple’s external posture through standards and regulatory engagement.

Location: San Francisco

Workplace: Onsite

Employment Type: Full time

Job Function: Cybersecurity

Seniority: Mid level

Key Responsibilities

•Drive the AI Security technical strategy and roadmap, defining how Ripple secures AI systems and embeds security controls across the AI development lifecycle.
•Design and implement security controls for LLM-integrated and agentic AI systems, including sandboxing, permission scoping, runtime monitoring, and containment of autonomous actions beyond authorized scope.
•Own AI security across the Controlled Agentic SDLC by establishing guardrails, AI provenance standards, dual-review requirements, and audit trail controls.
•Lead security review and risk assessment for AI integrations entering production, including LLM APIs, SaaS copilots, AI code editors, agentic workflows, MCP servers, and vendor-embedded AI.
•Build and scale Shadow AI detection to surface unsanctioned AI usage, enforce the AI acceptable use policy, and ensure AI workflows operate within an auditable perimeter.

Pay and Benefits

Salary: USD 232,000 - 290,000 annually

Perks:EquityHealth InsuranceRetirementParental LeaveLearning BudgetMobile PhoneWellness StipendPaid Leave

Key Requirements

•10+ years of Security Engineering experience with depth across at least two domains (e.g., Product Security, Cloud Security, Security Operations) and hands-on AI/ML security exposure.
•Strong understanding of AI/LLM security concepts including prompt injection, jailbreaks, data poisoning, model extraction, RAG manipulation, and agentic risks (tool poisoning, excessive agency, MCP server vulnerabilities).
•Experience securing agentic AI systems using approaches like sandboxing, permission scoping, human-in-the-loop design, and/or runtime monitoring for autonomous workflows.
•Fluency in core security domains such as cloud security on AWS, GCP, or Azure, CI/CD pipeline security, container/Kubernetes security, IAM, and API security—applied to AI contexts.
•Strong threat modeling skills using frameworks such as STRIDE, MITRE ATLAS, or OWASP LLM Top 10, and comfort applying them while threat/playbooks are still evolving.

Experience:10+ yearsFinTechCryptoSaaSAgentic AILLM security

Skills:Threat modelingCross-team influenceProblem-solvingTechnical strategyBuilder mindset

Languages:English

Tech Stack:AI securityArtificial intelligenceLLMsAgentic AIAgentic SDLCPrompt injectionJailbreaksData poisoningModel extractionRAGTool poisoningMCP serversSandboxingIdentity and permission scopingRuntime monitoringAudit trailSTRIDEMITRE ATLASOWASP LLM Top 10AWS

Company Brief

Ripple

Website

Loading job details...

Preparing the role view and application actions.

Ripple

1 month ago

Senior Staff Security Engineer, AI

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 hour agoStatus: Live

Job Summary

Location: San Francisco

Workplace: Onsite

Employment Type: Full time

Job Function: Cybersecurity

Seniority: Mid level

Key Responsibilities

•Drive the AI Security technical strategy and roadmap, defining how Ripple secures AI systems and embeds security controls across the AI development lifecycle.
•Design and implement security controls for LLM-integrated and agentic AI systems, including sandboxing, permission scoping, runtime monitoring, and containment of autonomous actions beyond authorized scope.
•Own AI security across the Controlled Agentic SDLC by establishing guardrails, AI provenance standards, dual-review requirements, and audit trail controls.
•Lead security review and risk assessment for AI integrations entering production, including LLM APIs, SaaS copilots, AI code editors, agentic workflows, MCP servers, and vendor-embedded AI.
•Build and scale Shadow AI detection to surface unsanctioned AI usage, enforce the AI acceptable use policy, and ensure AI workflows operate within an auditable perimeter.

Pay and Benefits

Salary: USD 232,000 - 290,000 annually

Perks:EquityHealth InsuranceRetirementParental LeaveLearning BudgetMobile PhoneWellness StipendPaid Leave

Key Requirements

•10+ years of Security Engineering experience with depth across at least two domains (e.g., Product Security, Cloud Security, Security Operations) and hands-on AI/ML security exposure.
•Strong understanding of AI/LLM security concepts including prompt injection, jailbreaks, data poisoning, model extraction, RAG manipulation, and agentic risks (tool poisoning, excessive agency, MCP server vulnerabilities).
•Experience securing agentic AI systems using approaches like sandboxing, permission scoping, human-in-the-loop design, and/or runtime monitoring for autonomous workflows.
•Fluency in core security domains such as cloud security on AWS, GCP, or Azure, CI/CD pipeline security, container/Kubernetes security, IAM, and API security—applied to AI contexts.
•Strong threat modeling skills using frameworks such as STRIDE, MITRE ATLAS, or OWASP LLM Top 10, and comfort applying them while threat/playbooks are still evolving.

Experience:10+ yearsFinTechCryptoSaaSAgentic AILLM security

Skills:Threat modelingCross-team influenceProblem-solvingTechnical strategyBuilder mindset

Languages:English

Company Brief

Ripple

Website