Why This Role Stands Out
Leverage your expertise in AI and Python to drive innovation as a Senior AI Engineer at EPAM Systems, shaping the future of enterprise agent development on AWS Bedrock AgentCore. This hybrid role offers significant growth potential by allowing you to own a cutting-edge orchestration framework, perfect for experienced engineers passionate about scalable AI solutions and collaborative team environments.
Quick Overview
Job Description
We are looking for a Senior AI Engineer to join our team and own the Agent Orchestration Framework, covering multi-agent orchestration patterns, checkpointing/state management, and human-in-the-loop workflow design as part of 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.
The platform standardizes agent development across the organization using LangGraph and Strands Agents on AWS AgentCore Runtime, providing a single-file developer experience where the platform handles runtime, tooling, observability, and deployment automatically.
Responsibilities Own the design and evolution of the Agent Orchestration Framework across the platform Design and implement multi-agent orchestration patterns such as supervisor/worker and fan-out/fan-in Build and maintain checkpointing and state management mechanisms within LangGraph workflows Architect human-in-the-loop (HITL) workflows to support enterprise approval processes Enable A2A agent delegation through the Agent Gateway Develop and maintain agent runtimes on AWS Bedrock AgentCore Runtime Collaborate with engineering teams to standardize agent development practices across the organization Ensure observability, reliability, and scalability of deployed agents in production environments Requirements 5+ years of experience in Python engineering Hands-on experience with LangGraph and LangChain for multi-step agent workflows Experience with AWS Bedrock AgentCore Runtime Experience with workflow orchestration tools such as Temporal or Airflow, or equivalent platforms Knowledge of stateful distributed system patterns, including checkpointing and idempotency Understanding of multi-agent orchestration patterns, including supervisor/worker and fan-out/fan-in designs Familiarity with human-in-the-loop (HITL) workflow design English proficiency at B2 level or higher Nice to have Experience evaluating AWS AgentCore Runtime maturity Familiarity with AWS Bedrock Memory API Experience integrating enterprise HITL approval workflows
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