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Chief Agentic AI Engineer
Job description
We are looking for a Chief Agentic AI Engineer to build autonomous agent systems at scale and steer decisions across runtime, memory, identity, tools, and observability. You will lead production-grade deployments using AWS Bedrock Agent. Core and agentic frameworks, shaping guardrails, evals, and reliability.
Responsibilities
Define the architecture for building, deploying, and operating autonomous agents across runtime, memory, identity, tools, and observability Champion the use of AWS Bedrock Agent. Core and the Strands Agents SDK across agent harnesses and production deployments Architect long-term memory and context-management systems that remain robust across multi-step engagements Develop and maintain MCP servers and tool integrations agents call, including recon, scanners, exploit primitives, and custom internal services Optimize reliability, cost, and latency of agent reasoning Establish standards for evals, tracing, and guardrails Requirements 7+ years of experience building production software, including 2+ year shipping LLM-based agents to production Expert proficiency in Python and hands-on use of an agentic framework such as Strands, Lang.
Graph, Claude Agent SDK, OpenAI Agents SDK, or CrewAI Working knowledge of AWS Bedrock Agent. Core primitives, including Runtime, Memory, Identity, Gateway, and Observability, or demonstrated ability to ramp up quickly Deep understanding of MCP, tool use, prompt/context engineering, memory architectures, and agent evaluation Demonstrated capability to design for production, including observability, guardrails, retries, cost control, and security boundaries English proficiency at B2 level or higher Nice to have Prior background in application security, web pentesting, or red-teaming Exposure to sandboxed code execution, browser agents, or autonomous tool orchestration
Description copied from EPAM Systems's careers page. Read the full posting before you apply.
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