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AI Cybersecurity Engineer
GRAILAI Cybersecurity Engineer designing and implementing GRAIL's Cybersecurity Program for secure AI systems and initiatives. Collaborating with cross-functional teams to ensure responsible and resilient AI adoption.
Tech Stack
Tools & technologiesAWSAzureCloudGoogle Cloud PlatformTerraform
About the role
Key responsibilities & impact- Build and maintain a secure reasoning layer for GRAIL data strategy
- Develop and refine healthcare-specific security detection models
- Implement and manage cryptographic Private Information Retrieval (PIR) systems
- Design data-layer protections to ensure server-side tampering is detected
- Deploy and maintain Terraform IaC across AWS multi-cloud environments
- Utilize XAI tools like LIME and SHAP to analyze model failure modes
- Design, build, and support AI/ML solutions and integrations
- Evaluate and secure AI platforms in AWS Bedrock
- Lead development of AI security controls, guardrails, and governance frameworks
- Perform threat modeling and risk assessments for AI/ML systems
- Partner with engineering teams to enable secure AI development practices
- Assess and mitigate risks related to LLMs
- Contribute to secure architecture patterns for AI-enabled applications
- Support security reviews, testing, and validation of AI use cases
- Collaborate with cloud, data, and application teams to ensure secure deployment of AI capabilities
- Evaluate and onboard AI vendors and tools
- Promote awareness and adoption of secure AI usage practices across the organization
- Remain current on emerging AI and security risks
- Ensure alignment and compliance with industry standards and advanced security architectures
Requirements
What you’ll need- Strong hands-on experience with AI/ML technologies, LLMs, or AI development tools
- 3–5+ years of experience in security engineering, application security, or cloud security
- Experience performing threat modeling, security architecture design, and secure code review or testing
- Experience developing AI solutions within IDEs, utilizing AI code assistants
- Experience working with LLM APIs (OpenAI, Anthropic, etc.)
- Familiarity with AI frameworks such as LangChain, LlamaIndex, or similar
- Understanding of AI/ML lifecycle and prompt engineering
- Familiarity with AI security risks such as prompt injection, data leakage, and model misuse
- Experience working in cloud environments (AWS, Azure, or GCP)
- Familiarity with secure development practices (DevSecOps)
- Working knowledge of OWASP Top 10 and application security principles
- Strong collaboration and communication skills
Benefits
Comp & perks- flexible time-off or vacation
- a 401(k) retirement plan with employer match
- medical, dental, and vision coverage
- carefully selected mindfulness programs
ATS Keywords
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Hard Skills & Tools
AI/ML technologiesLLMscryptographic Private Information Retrieval (PIR)TerraformAWSXAI toolsthreat modelingsecurity architecture designsecure code reviewAI frameworks
Soft Skills
collaborationcommunicationleadership