AI Engineer (AI Data Privacy, Security & Governance)

This role safeguards GenAI-enabled applications, including LLM-powered workflows, RAG pipelines, plugins, skills, and autonomous agents, by embedding data protection, security guardrails, and responsible AI governance across the development lifecycle. This role supports SDLC documentation across all phases, with a focus on data privacy, security guardrails, governance, compliance, and risk management. It also works with users to define requirements and support applications in production. What You’ll Do + Design and implement data privacy controls, including PII/PHI detection, redaction, and data minimization. + Build security guardrails, including prompt-injection defense, jailbreak prevention, and output filtering. + Establish governance for plugins, skills, and agents, including registration, approval, and lifecycle management. + Review and vet third-party plugins, skills, and agent tools for security, privacy, and compliance risks. + Define and enforce access controls, authentication, and least-privilege permissions for AI components. + Implement guardrails for autonomous agents, including action scoping, tool-use restrictions, and human-in-the-loop approval. + Apply data classification, retention, and residency policies across GenAI data flows. + Monitor AI systems for policy violations, data leakage, and anomalous plugin, skill, or agent behavior. + Maintain audit trails and logging for plugin, skill, and agent activity. + Support compliance with regulations and frameworks, including GDPR, CCPA, and the EU AI Act. + Provide Level II production support for security, privacy, and governance incidents. + Support incident response, including containment, escalation, and remediation.

Requirements + 4+ years of experience in IT or a related field. + 2+ years of software engineering experience. + 1+ year of experience in AI security, data privacy, or governance. + Experience with AI coding agent-augmented development. + Experience with data privacy techniques, including PII detection, redaction, and anonymization. + Experience with Python, Java, C#, JavaScript, or SQL. + Experience building and securing applications. + Knowledge of cloud platforms, containers, and CI/CD practices. + Understanding of SDLC, APIs, and system architecture. + Knowledge of databases and data integration. + Understanding of LLM fundamentals and token behavior. + Knowledge of security guardrails, including prompt-injection and jailbreak defenses. + Experience governing plugins, skills, and agents, including registration and lifecycle management. + Knowledge of identity and access management, including authentication and least-privilege design. + Familiarity with AI risk frameworks, including the NIST AI RMF and OWASP LLM Top 10. + Knowledge of privacy and compliance regulations, including GDPR, CCPA, and the EU AI Act. + Experience with observability practices, including logging, tracing, and audit trails. + Experience with Azure, AWS, or GCP. + Strong communication and requirements-gathering skills. Preferred Generative AI Skills + Experience with AI governance platforms and policy-as-code frameworks. + Experience with secrets management, encryption, and data loss prevention (DLP). + Experience with red-teaming and adversarial testing of LLM applications. + Experience designing agent guardrails, including tool sandboxing and action approval. + Experience with content moderation and output safety filtering. + Experience with security incident handling, including containment and forensics.

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