Information Technology_USA - USA_Engineer

**Please strictly adhere to the following resume naming convention:ALL CAPS, NO SPACES BETWEEN UNDERSCORESPTN_US_GBAMSREQID_CandidateBeelineIDExample: PTN_US_9999999_SKIPJOHNSON0413: - MSP Owner: Michelle LeeLocation: Dallas, TX / HybridDuration: 6 monthsGBaMS ReqID: 10941209SummaryBuild and scale a production multi-agent AI platform serving thousands of internal users across multiple business units. Monthly release cadence, real users, real latency, real cost.Responsibilities• LLM-driven orchestrator that routes user intent across a portfolio of specialized agents - delegation, memory, response validation, capability discovery.• Agent selection layer - hybrid retrieval (vector RAG over a capability registry) plus closed-set LLM selection with JSON-schema-constrained outputs.• Multi-agent SDK / gateway - FastAPI service hosting many agents behind path-prefix routing, per-agent tool registries, session-scoped conversational context.• Tool-driven agents - 15-30 tools per agent composed dynamically by an LLM; owns tool contracts, guardrails, and evaluation.• Data API layer - parameterized endpoints between agents and databases; LLMs never touch DBs directly.• Partner-team onboarding - versioned A2A contract, bring-your-own-agent registration, auto re-embedding.Core AI Engineering• Production LLM systems: RAG, tool/function-calling loops, structured outputs, hallucination guards, closed-set selection.• Multi-agent orchestration: A2A protocols, session affinity, human-in-the-loop gating, kill switches, graceful degradation.• Vector search + embeddings at scale (sub-second retrieval over thousands of docs).• Evaluation & safety: PII/PHI masking, audit trails, feedback-loop instrumentation, offline + online eval.Platform / Infrastructure• Python 3.11+, FastAPI, async I/O, Pydantic.• Modern LLM stacks (Gemini, GPT, Claude) and agent frameworks (LangGraph, Agent SDKs).• Cloud (GCP or AWS): Kubernetes, object storage, workflow orchestration, Vertex/Bedrock-class services.• Redis, MongoDB, Oracle/Postgres, SSO + RBAC.• Observability: Prometheus, structured JSON logs, per-decision audit trails, p95 latency SLOs in seconds.Skills: Digital : Python~Digital : Machine Learning~Digital : Artificial Intelligence(AI)~Generative AIExperience Required: 10 & Above