Platform Engineer – Memory Retention & Compliance

We are looking for a Platform Engineer to design and implement memory retention and compliance capabilities for an enterprise AI Agent Platform being built from the ground up.

The role will focus on ensuring that agent memory is managed throughout its lifecycle in accordance with privacy, data retention, and compliance requirements, including automated expiration, user-driven deletion, data classification, and auditable cleanup processes.

Our client is a large global enterprise operating across multiple markets, with a complex technology landscape and a strong focus on digital transformation and innovation. The organization is actively investing in modern cloud, data, and AI capabilities to enable scalable, secure, and highly automated solutions across its business.

The project is focused on building an enterprise-grade AI Agent Platform from the ground up. The platform will provide a standardized foundation for developing, deploying, orchestrating, securing, and observing AI agents across multiple teams and use cases.

The initiative covers the full agent lifecycle and brings together agent orchestration, observability, security, governance, integrations, evaluation, and platform engineering. Engineers joining the project will have an opportunity to influence key architectural and technical decisions and contribute to a new platform rather than maintaining an existing solution.

• Design and implement retention policies for agent memory, including expiration and lifecycle rules for different memory types.
• Configure and manage AWS AgentCore Memory capabilities supporting memory lifecycle management. AgentCore Memory supports both short-term session context and long-term knowledge retention. [docs.aws.amazon.com], [docs.aws.amazon.com]
• 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 when required.
• 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.

• Agent memory retention policies — TTL configuration, episodic memory expiration, summary memory lifecycle

• GDPR compliance for agent memory — user deletion handler, right to erasure, audit trail

• AWS AgentCore Memory configuration — TTL settings, namespace policies, access controls

• Memory data classification — determine sensitivity, encryption requirements, retention periods

• Agent memory cleanup — automated expiration, manual purge procedures

• 4+ years platform or compliance engineering

• Data retention policy implementation

• GDPR/privacy compliance for user data

• TTL and lifecycle management for cloud storage

• AWS AgentCore Memory retention configuration

• Privacy engineering for AI systems

• Audit trail and compliance logging

• Cross-region data residency requirements