Agentic AI Architect

Role Summary Owns the end-to-end AI agent architecture for Client's Agent Factory. Defines reusable patterns, orchestration standards, model selection, tool integration, security, and technical governance, ensuring modularity, scalability, and reuse across enterprise functions. Key Responsibilities • Design multi-agent reference architectures using Gemini Enterprise, ADK, Agent Engine, A2A, and ClientP. • Define agent blueprints, composable design standards, and the Client Agent Library structure. • Establish orchestration, memory, RAG, and tool-invocation strategy. • Guide model selection (Gemini Pro / Flash / Flash-Lite) balancing cost, latency, and quality. • Own security architecture (IAM, VPC-SC, Model Armor) and observability standards. • Review and approve all agent-level technical designs and integration approaches. Mandatory (Must-Have) Skills • Deep expertise in Gemini Enterprise, Vertex AI, ADK, Agent Engine, A2A, ClientP, Model Garden. • Strong RAG, vector DB, embeddings, and knowledge-graph design. • Secure enterprise-scale AI platform architecture (IAM, VPC-SC, DLP, guardrails). • Microservices, containers (GKE/Cloud Run), API design. Preferred (Good-to-Have) Skills • Multi-agent systems and agentic orchestration patterns. • Cost/latency optimization and model tiering. • Prior GSI / large enterprise AI transformation experience. Experience & Certifications • 12+ years IT with 3+ years in AI/GenAI/agentic architecture.