Enterprise AI Governance & Trust Layer Engineer

This is a remote position.

• Employment Type: Contract
  
• Work Mode: Remote
  
• Location: Offshore
  
• Total Experience Required: 5 to 9 years
  
• Relevant Experience Required: 3+ years of experience engineering data privacy layers, AI governance controls, and security trust layers between enterprise networks and LLMs
  
• Mandatory Certification: Certified Information Systems Security Professional (CISSP), Certified DevSecOps Professional (CDP), or AWS Certified Security - Specialty
  

• Design and deploy enterprise AI Trust Layers and governance middleware, orchestrating data masking boundaries between internal relational databases and public foundational models.
  
• Configure real-time Personally Identifiable Information (PII) scrubbers, utilizing advanced regex, Named Entity Recognition (NER), and tokenization engines to mask sensitive fields before LLM submission.
  
• Implement robust data compliance and sovereignty controls, building policy-as-code guardrails to align model access scripts with strict regional privacy mandates (e.g., GDPR, CCPA, HIPAA).
  
• Build automated AI transaction audit logs, setting up immutable data logging targets, token usage trackers, and system monitoring loops to track model input-output histories for forensic validation.
  
• Integrate deep-level toxicity and bias filtering panels, deploying custom moderation models and classification gates to block harmful, inappropriate, or non-compliant model generations.
  
• Establish anti-prompt-injection defensive rings, writing input parsing scripts to isolate, analyze, and intercept adversarial jailbreaks, system instruction overriding attempts, and malicious payloads.
  
• Collaborate with security and data engineering squads, configuring custom API proxy setups, secure OAuth 2.0 validation pathways, and centralized data access controls (RBAC) across integrated LLM networks.
  

Requirements

• engineering experience, with at least 3+ dedicated years actively designing, building, and maintaining AI safety pipelines.
  
• Strong technical mastery of Python, regular expressions, automated data classification frameworks, API architecture design, and cloud security frameworks.
  
• Deep structural understanding of prompt injection vulnerabilities, data drift behaviors, token transmission limits, and zero-data-retention API policies.
  
• Mandatory certification: CISSP, CDP, or a dedicated Cloud Security Specialty credential.
  

• Prior experience implementing Salesforce Einstein Trust Layer controls or similar pre-built enterprise platform AI safety gates.
  
• Familiarity with vector embeddings or custom text classification model tuning to detect nuanced enterprise intellectual property leaks.