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Senior AI Security Engineer
RemoteFull-timeSecurity Engineering
Design and implement security, privacy, and governance controls for enterprise generative AI systems. Build protections for sensitive data and LLM interactions, and collaborate with security and data engineering teams. The role is remote and described as a contract engagement with an offshore work:
Responsibilities
- Design and deploy governance middleware and trust layers between enterprise systems, applications, and LLMs
- Implement real-time PII detection and masking using regular expressions, named entity recognition, tokenization, and data classification
- Develop policy-as-code controls for privacy, compliance, and data sovereignty
- Build immutable audit trails for AI inputs and outputs, token usage, access activity, monitoring, and forensic analysis
- Implement toxicity, bias, and content-safety controls
- Defend against prompt injection, jailbreaks, malicious payloads, and attempts to override system instructions
- Configure secure API proxies, OAuth 2.0 flows, role-based access control, and centralized access controls
- Integrate governance controls into enterprise AI workflows and strengthen security with technical teams
Requirements
- At least 5 years of engineering experience, including at least 3 years building or maintaining AI safety, privacy, governance, or security pipelines
- Strong proficiency in Python, regular expressions, automated data classification, API architecture, and cloud security frameworks
- Understanding of AI security risks such as prompt injection, jailbreaks, data leakage, data drift, token transmission constraints, and zero-data-retention API models
- Experience engineering privacy, governance, or security trust layers between enterprise systems and LLM applications
- Strong understanding of authentication, authorization, secure API design, data protection, and enterprise access controls
- Ability to translate privacy and security requirements into technical controls and automated guardrails
- CISSP, Certified DevSecOps Professional, or relevant cloud security specialty certification
Nice to have
- Experience with Salesforce Einstein Trust Layer or comparable enterprise AI safety platforms
- Familiarity with vector embeddings and custom text-classification models for identifying enterprise data leaks
Benefits
- Fully remote working arrangement
- Contract engagement with an offshore work model
- Technical ownership across AI governance middleware, privacy boundaries, monitoring, and security architecture
- Opportunity to work on enterprise AI governance, privacy, security, and trust infrastructure