python developer for AI agents

The Enterprise Agent Development Platform is a production-grade, cloud-native ecosystem that enables engineering teams to define, orchestrate, deploy, and observe AI agents at scale. It 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. The platform aims to reduce agent development from months to days while enforcing consistent security, quality, and governance standards.

• Integrate AgentCore Memory into platform agent templates and helper libraries
• Implement write-on-turn functionality to store session events
• Implement retrieve-on-turn functionality to fetch relevant context
• Design and build memory namespace architecture for per-agent isolation and per-user scoping
• Develop Python helper libraries to support memory-enabled agents across the platform
• Enable memory activation through configuration rather than custom code in agent templates
• Use AWS AgentCore Memory API to create, query, update, and delete memory records
• Build and maintain API integrations for stateful services
• Manage session persistence and context continuity across agent interactions

• 7+ Years of backend engineering experience with AI/ML systems
• Hands-on experience integrating agent memory in a production agentic AI project, such as AWS AgentCore Memory API (write-on-turn/retrieve-on-turn), memory namespace design, or agent template memory configuration
• Expertise in Python SDK development
• Skills in API integration for stateful services
• Proficiency in session management and context persistence
• English proficiency at B2 level or higher
• Будет плюсом: familiarity with AWS AgentCore Memory SDK usage, knowledge of LangChain memory integration, background in agent framework development (LangGraph, Crew), understanding of conversational AI context handling

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