Role Overview: We are seeking a hands-on Lead Agentic AI & GenAI Engineer to architect and productionize secure, autonomous and human-supervised AI agents. The role emphasizes agent design, LLM application engineering, AI-assisted software delivery, evaluation, safety, and production operations, with sufficient data integration skills to connect governed enterprise sources.
Work Location: Charlotte, NC
Key Responsibilities
• Architect single-agent and multi-agent solutions using Google ADK, LangGraph/LangChain, Microsoft Semantic Kernel, AutoGen, OpenAI Agents SDK.
• Design agent workflows using Model Context Protocol (MCP), function calling, structured outputs, reusable skills, planning, state, memory, A2A handoffs, and human approval gates.
• Use Claude Code, GitHub Copilot agent mode/coding agent, Devin, Cursor, OpenAI Codex for implementation, testing, refactoring, documentation, and pull-request workflows.
• Build grounded enterprise AI experiences using advanced RAG, hybrid retrieval, reranking, knowledge graphs, citations, context engineering, and governed model access.
• Engineer reliable Python and TypeScript agent services with asynchronous execution, retries, checkpointing, idempotency, rollback, escalation, and long-running workflow patterns.
• Implement agent evaluation and LLMOps using task-success benchmarks, ARIZE tracing, prompt/version management, latency and token-cost controls, and production SLOs.
• Apply enterprise AI security including prompt-injection defense, least-privilege tool access, sandboxing, PII protection, content safety, auditability, red teaming, and policy enforcement.
• Integrate agents with enterprise APIs, databases, events, documents, and Systems of Record, partnering with product, operations, risk, cyber, architecture, and platform teams.
