Senior Platform Engineer

Description

We are seeking a Senior Platform Engineer to own agent memory retention policies, TTL configuration, and GDPR compliance within our Enterprise Agent Development Platform — a production-grade, cloud-native ecosystem that enables engineering teams to define, orchestrate, deploy, and observe AI agents at scale. This platform standardizes agent development across the organization using LangGraph and Strands Agents on AWS AgentCore Runtime, spanning agent framework design, runtime architecture, marketplace integration, CI/CD automation, and enterprise-grade observability, reducing agent development from months to days while enforcing consistent security, quality, and governance standards. Responsibilities Define and maintain agent memory retention policies, including TTL configuration, episodic memory expiration, and summary memory lifecycle Ensure GDPR compliance for agent memory systems, including user deletion handlers, right to erasure processes, and audit trail maintenance Configure AWS AgentCore Memory settings, including TTL parameters, namespace policies, and access controls Classify memory data according to sensitivity, encryption requirements, and retention periods Manage agent memory cleanup processes, including automated expiration and manual purge procedures Collaborate with engineering teams to embed compliance and governance standards into agent development workflows Monitor and audit memory retention practices to ensure alignment with regulatory requirements Requirements 3+ years of experience in platform or compliance engineering Hands-on experience with agent memory systems in a production agentic AI project, such as implementing memory retention/TTL policies, memory lifecycle management, or GDPR-style data governance for AI agents Expertise in data retention policy implementation, GDPR/privacy compliance for user data, and TTL and lifecycle management for cloud storage English proficiency at B2 level or higher Nice to have Familiarity with AWS AgentCore Memory retention configuration Background in privacy engineering for AI systems Knowledge of audit trail and compliance logging Understanding of cross-region data residency requirements

Requirements

• 3+ years of experience in platform or compliance engineering

• Hands-on experience with agent memory systems in a production agentic AI project, such as implementing memory retention/TTL policies, memory lifecycle management, or GDPR-style data governance for AI agents

• Expertise in data retention policy implementation, GDPR/privacy compliance for user data, and TTL and lifecycle management for cloud storage

• English proficiency at B2 level or higher

Responsibilities

• Define and maintain agent memory retention policies, including TTL configuration, episodic memory expiration, and summary memory lifecycle

• Ensure GDPR compliance for agent memory systems, including user deletion handlers, right to erasure processes, and audit trail maintenance

• Configure AWS AgentCore Memory settings, including TTL parameters, namespace policies, and access controls

• Classify memory data according to sensitivity, encryption requirements, and retention periods

• Manage agent memory cleanup processes, including automated expiration and manual purge procedures

• Collaborate with engineering teams to embed compliance and governance standards into agent development workflows

• Monitor and audit memory retention practices to ensure alignment with regulatory requirements

Seniority

• Senior

Nice to have

• Familiarity with AWS AgentCore Memory retention configuration

• Background in privacy engineering for AI systems

• Knowledge of audit trail and compliance logging

• Understanding of cross-region data residency requirements