AI Engineering for Compliance Agents
Design advanced AI agents and integrate them with regulatory frameworks. Bridges foundational AI knowledge and specialized engineering skills for compliance environments. Covers agent design, memory systems, RAG pipelines, MCP integration, and governance frameworks.
Learning Outcomes
- ✓Design and deploy compliance-focused AI agents
- ✓Build memory systems for audit trails and historical tracking
- ✓Develop RAG pipelines for regulatory documents
- ✓Integrate AI tools with compliance data sources and APIs via MCP
- ✓Establish AI governance frameworks for regulated environments
- ✓Apply prompt architecture patterns for regulatory analysis
Course Modules
Module 1: AI Fundamentals for Compliance Professionals
PT3HCore AI concepts, LLM architectures, and how they apply to compliance workflows. Understanding tokens, context windows, and model capabilities.
Module 2: Prompt Architecture for Regulatory Analysis
PT3HMove beyond basic prompting to systematic prompt design. Chain-of-thought reasoning, few-shot patterns, and structured output for compliance queries.
Module 3: Agent Memory and Context Management
PT4HDesign memory systems that maintain audit context across sessions. Vector databases, session stores, and compliance-specific retrieval patterns.
Module 4: RAG Pipelines for Regulatory Frameworks
PT4HBuild retrieval-augmented generation systems over regulatory documents. Chunking strategies, embedding models, and accuracy validation for compliance data.
Module 5: MCP Integration with Compliance APIs
PT3HConnect AI agents to compliance data sources using Model Context Protocol. Query 692+ frameworks, map controls, and run gap analyses programmatically.
Module 6: AI Governance and Security
PT3HImplement guardrails, access controls, and audit logging for AI systems in regulated environments. Data privacy, model risk management, and responsible AI.
Module 7: Automated Regulatory Reporting
PT3HDesign AI-powered reporting pipelines that generate compliance reports, gap analyses, and board-ready summaries from framework data.
Module 8: Advanced Agent Techniques
PT4HMulti-agent orchestration, tool use patterns, and autonomous compliance workflows. Building reliable agents that operate within defined boundaries.
Module 9: Case Study: ISO 27001 and SOC 2
PT3HEnd-to-end implementation using ISO 27001:2022 and SOC 2 frameworks. Build agents that map controls, identify gaps, and generate remediation plans.
Module 10: Case Study: GDPR and NIST CSF
PT3HCross-framework compliance with GDPR and NIST Cybersecurity Framework. Automated data protection impact assessments and control mapping.
Module 11: Ethics and Responsible AI in Compliance
PT3HBias detection, explainability requirements, and ethical considerations when deploying AI in compliance and audit functions.
Module 12: Leadership and Transformation
PT4HBuilding the business case for AI in compliance. Change management, ROI measurement, and scaling AI engineering across the organization.
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