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Mid-level metro role with specialist LLM/agent skills reduces broad applicant pool.
Requires specialized LLM/agent engineering and AMS/ITSM expertise, limiting cross-industry transferability.
Explicit 5+ years and 2+ years GenAI plus specific agent frameworks and engineering requirements.
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Design, build, and optimize reusable AI agents and workflows targeting operational use cases like ticket analysis, knowledge mining, SLA tracking, and runbook automation.
Ensure AI agents are accurate, secure, testable, observable, and continuously improved using production telemetry, evaluation metrics, and SME feedback.
Deliver agent packaging, version control, unit testing, error handling, and observability to support production reliability and post-deployment refinement.
5+ years in software, automation, or platform engineering with 2+ years hands-on development of GenAI, LLM, RAG, or AI agent applications (AMS/ITSM experience preferred).
Experience with Agent Builder or enterprise agent development platforms involving multi-agent orchestration and deployment.
Proficiency in agent frameworks like LangChain, LangGraph, AutoGen, CrewAI and core software engineering skills: Python, REST APIs, Git, CI/CD, unit testing.
Understanding of AMS/ITSM systems including ServiceNow data, ticket lifecycle, CMDB, SLAs, runbook automation.
Experienced in full lifecycle delivery of AI agents from design and prompt engineering to production testing and release.
Comfortable working with complex multi-agent workflows and advanced agentic patterns such as planner, executor, memory, and critic.
Capable of embedding governance mechanisms including human-in-the-loop approvals, audit logs, performance metrics, and hallucination minimization to ensure agent reliability.