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описание
The project is building an enterprise-grade AI Agent Platform from the ground up. The platform provides a standardized foundation for developing, deploying, orchestrating, securing, and observing AI agents across multiple teams and use cases. It covers the agent lifecycle, including orchestration, observability, security, governance, integrations, evaluation, and platform engineering.
задачи
Design and implement retention policies and lifecycle rules for different types of agent memory;
Configure and manage AWS AgentCore Memory capabilities for memory lifecycle management, supporting short-term session context and long-term knowledge retention;
Implement automated memory expiration and cleanup workflows based on defined retention policies;
Build user deletion and right-to-erasure mechanisms to support GDPR and privacy requirements;
Define and implement manual purge procedures for agent memory;
Establish memory data-classification rules, including sensitivity levels, encryption requirements, and retention periods;
Ensure appropriate namespace isolation and access-control patterns for memory data;
Maintain audit trails and compliance logging for memory lifecycle and deletion operations;
Support retention strategies for episodic, summary, and other long-term agent memory;
Implement controls supporting data residency and cross-region compliance requirements;
Collaborate with security, platform, and governance teams to establish privacy and retention standards for AI agents.
требования
4+ Years of platform or compliance engineering experience;
Experience implementing data retention policies;
Experience with GDPR/privacy compliance for user data;
Experience with TTL and lifecycle management for cloud storage;
Nice to have: AWS AgentCore Memory retention configuration, privacy engineering for AI systems, audit trail and compliance logging, cross-region data residency requirements.
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