Pierce Professional Resources

Security Engineer

• Ensure advanced AI systems are designed and operated with the highest levels of security, compliance, and reliability.
• Define threat models for AI workflows, including data misuse, privilege escalation, and model abuse.
• Implement guardrails and access controls (DLP, secret management, RBAC/ABAC) for AI pipelines.
• Enforce bounded autonomy and human-in-the-loop approvals for critical agent actions.
• Build monitoring systems to detect model drift, hallucinations, and anomalous behavior.
• Integrate AI decision-logging into enterprise SIEM platforms for traceability and compliance.
• Lead red-team adversarial testing to expose vulnerabilities and strengthen resilience.
• Develop and maintain incident response runbooks coordinating engineering and security teams.

AI Security Engineer

AI Engineer

• Design, implement, and optimize advanced AI systems balancing quality, performance, and cost.
• Architect inference and RAG pipelines; design manager/worker agent patterns with deterministic fallback mechanisms for reliability.
• Build robust evaluation harnesses and develop simulation-based training pipelines to improve model robustness.
• Tune AI systems across quality, latency, and cost dimensions for scalable production performance.
• Run A/B tests and continuous feedback loops to measure system performance and guide improvements.
• Collaborate with product and design teams to ensure AI outputs integrate into workflows with intuitive, high-quality UX.

Risk

• We are seeking a Governance & Risk Specialist to establish and oversee the governance frameworks that ensure safe, compliant, and responsible use of AI systems.
• Classify risks for AI systems and complete Data Protection Impact Assessments (DPIA) and Privacy Impact Assessments (PIA).
• Maintain “agent cards” that record purpose, limitations, lineage, and performance characteristics of deployed AI agents.
• Map organizational practices to regulatory and industry frameworks (NIST AI RMF, ISO standards, EU AI Act, GDPR, etc.).
• Operate governance checkpoints across the AI lifecycle, ensuring audit trails for key decisions.
• Require joint human+agent metrics and evidence of adoption to validate responsible use.
• Ensure contracts with vendors include appropriate language to limit ownership and liability for AI-related incidents.
• Partner with engineering, security, and legal teams to refine governance practices as AI technologies and regulations evolve.

AI Security Engineer

AI Engineer

Governance and Risk Specialist