Cross River

AI Security Engineer

Cross River

full-time

Posted on:

Location Type: Hybrid

Location: Jerusalem • Israel

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Tech Stack

AWSAzureCloudGRPCKubernetesPythonSDLCTerraformTypeScript

About the role

  • Design enterprise AI guardrails across Azure and AWS (e.g., Azure AI Studio/Azure OpenAI, Amazon Bedrock/SageMaker): content filtering, PII redaction, prompt/response validation, and policy enforcement services.
  • Implement data minimization controls for GenAI/RAG workloads: context filtering, least‐privileged retrieval, document-level ACL enforcement, vector store hardening, and secure token/secret handling.
  • Threat model AI systems (apps, agents, RAG, fine-tuning pipelines) using frameworks like STRIDE and the OWASP Top 10 for LLM Apps; define misuse scenarios (prompt injection/jailbreaks/data exfiltration) and build mitigations.
  • Build monitoring and telemetry: privacy-preserving prompt/response logging, sensitive-data detection, safety/eval dashboards, drift/abuse signals, and incident hooks into our SIEM.
  • Integrate AI security into the SDLC: reusable libraries, pre-commit checks, CI/CD gates, policy-as-code, and secure-by-default reference architectures for product teams.
  • Evaluate third‑party AI vendors and internal apps: security reviews, data residency and retention requirements, SSO/SCIM integrations, DPA/TPRM inputs, and continuous control testing.
  • Partner across Security, Data, Privacy, and Engineering to map AI controls to FFIEC, SOC 2, and PCI DSS; document control evidence for audits.
  • Lead/participate in AI red‑teaming: automated jailbreak/prompt‑injection tests, safety benchmarks, purple‑team exercises, and response playbooks for AI incidents.
  • Enable the org with concise guidelines, examples, and training on safe AI development and usage.

Requirements

  • 5+ years in Security Engineering/AppSec/Cloud Security (or similar), including 1–2+ years securing AI/ML or data‐intensive systems (GenAI preferred).
  • Hands‐on experience with AWS and/or Azure and modern app stacks (Python/TypeScript, REST/gRPC, containers/Kubernetes, IaC such as Terraform).
  • Practical understanding of LLM attack surfaces (prompt injection, data leakage via tools, training/fine‑tune poisoning, model supply chain) and mitigation patterns.
  • Familiarity with identity and access for AI workloads (OAuth2/OIDC, service principals, role tokens, PIM), and secure secret management/KMS.
  • Experience implementing observability/telemetry and routing findings to SIEM; comfort balancing privacy with traceability.
  • Ability to translate controls into developer-friendly libraries, docs, and CI/CD checks; strong written communication in English and Hebrew.
  • Comfort working in a regulated environment and mapping controls to frameworks (FFIEC, SOC 2, PCI DSS).
Benefits
  • Flexible hybrid work model: three days a week at our Jerusalem office
  • Monthly wellness reimbursement – from therapy to gel manicure, it's up to you
  • Full Keren Hishtalmut, private health and dental insurance
  • Volunteer days, donation matching, Yoga and Pilates
  • A supportive, collaborative culture that puts our people first
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
AI guardrailsdata minimization controlsthreat modelingmonitoring and telemetryAI security integrationsecurity reviewsAI red-teamingobservabilitysecure secret managementCI/CD
Soft Skills
strong written communicationcollaborationguideline developmenttraining