Lead Python Backend Engineer

EPAM Systems; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

EPAM Systems is seeking a Lead Python Backend Engineer to join our team building an Enterprise Agent Development Platform. You will design and implement memory-enabled backend services, focusing on scalable, cloud-native architecture on AWS.

You will integrate AgentCore Memory, develop Python SDKs, and ensure robust session management and context persistence across agent interactions. Strong Python and API integration skills are essential.

Qualifications

• 7+ years of backend engineering experience with AI/ML systems.
• Hands-on experience integrating agent memory in production AI projects.
• Expertise in Python SDK development and API integration.
• Proficient in session management and context persistence.
• English proficiency at B2 level or higher.

Responsibilities

• 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
• Work with 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

Skills

Python

AI/ML systems

API integration

Session management

SDK development

English proficiency

Tools

AWS

AgentCore Memory SDK

LangGraph

Job description

We are looking for a Lead Python Backend Engineer to join our team building an Enterprise Agent Development Platform — a production-grade, cloud-native ecosystem that enables engineering teams to define, orchestrate, deploy, and observe AI agents at scale. The platform standardizes agent development across the organization using LangGraph and Strands Agents on AWS AgentCore Runtime. The initiative spans 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

• 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
• Work with 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

Requirements

• 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

Nice to have

• 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