Lead Agentic AI Engineer

We are seeking a Lead Agentic AI Engineer to design, build, and operate scalable autonomous agent systems for production AI deployments. You will drive key decisions across runtime, memory, identity, tools, and observability while leading adoption of Amazon Bedrock AgentCore and related SDKs. Responsibilities Architect end-to-end systems to build, deploy, and run autonomous agents across runtime, memory, identity, tools, and observability Lead adoption of AWS Bedrock AgentCore and the Strands Agents SDK to power agent harnesses and production releases Design long-term memory and context-management capabilities that support sustained multi-step engagements Build and maintain MCP servers and agent tool integrations such as recon tools, scanners, exploit primitives, and internal custom services Optimize agent reasoning for higher reliability, improved cost-efficiency, and faster execution Define standards for evaluations, tracing, and guardrails Requirements Proven track record with 5+ years building production software, including 2+ year deploying LLM-based agents to production Expert Python skills and hands-on experience with agentic frameworks like Strands, LangGraph, Claude Agent SDK, OpenAI Agents SDK, or CrewAI Hands-on knowledge of AWS Bedrock AgentCore components—Runtime, Memory, Identity, Gateway, and Observability—or the ability to ramp up quickly Solid background in MCP, tool use, prompt/context engineering, memory architectures, and agent evaluation methods Deep understanding of production-grade design, including observability, guardrails, retry logic, cost management, and security boundaries English proficiency at B2 (Upper-Intermediate) level or higher Nice to have Experience with application security, web pentesting, or red-teaming Familiarity with sandboxed code execution, browser agents, or autonomous tool orchestration