Gen AI Architect

Job Summary Rapidly assess the customer landscape, design and implementation by understanding their processes, systems, data, and pain points to identify and implement high-impact GenAI/agentic opportunities. Define and own the end-to-end solution and technical architecture covering model selection, agent design, data ingestions, integration, services, guardrails, evaluation framework, and cost/security posture. Lead the team hands‑on through implementation, setting engineering and prompt‑engineering standards, unblocking hard problems, and driving an iterative measure‑improve‑ship cadence. Collaborate with business, IT, security, and engineering stakeholders to manage expectations, communicate risks, align on goals, and keep delivery on track. Own end‑to‑end delivery and adoption, instrument success metrics, and establish a post‑go‑live operating model that sustains measurable productivity gains in production. Required Skills Architecting, solutioning, and implementing scalable multi‑agent orchestrated systems leveraging LLMs, LangChain/LangGraph, ACP, and RAG, with strong capabilities in agent design patterns, workflow orchestration, context/memory engineering, prompt and tool integration, and enterprise‑grade observability, governance, and reliability. Python, Data Ingestion, Data Pipeline, Vector DB. Azure AI Foundry, Azure AI Service (or Similar services). #J-18808-Ljbffr TechDigital Group