AI Engineer (AI Data Privacy, Security & Governance)

Responsibilities

• Analyze, design, program, debug, test, implement, and support the privacy, security, and governance controls that protect generative AI technologies.
• Safeguard 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.
• Support SDLC documentation across all phases, with a focus on data privacy, security guardrails, governance, compliance, and risk management.
• Work with users to define requirements and support applications in production.
• 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.

Qualifications

• 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.
• Knowledge of 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.