Agent AI Architect

Key Responsibilities

·         Architect end-to-end Agentic AI platforms and multi-agent ecosystems.

·         Define orchestration, reasoning, memory, planning, RAG, MCP and tool-integration patterns.

·         Design secure cloud-native solutions using Vertex AI, Cloud Run, GKE, Cloud Spanner and Vector Search.

·         Establish AI governance, guardrails, observability, security, compliance and cost controls.

·         Translate business requirements into architecture and design-ready documentation.

·         Lead architecture reviews, technical decisions and stakeholder discussions across business and engineering teams.

Required Skills & Experience

·         10–15 years of architecture or senior engineering experience, including strong AI solution architecture exposure.

·         Expertise in multi-agent architecture, agent orchestration, LLMs, RAG, grounding, MCP and knowledge graphs.

·         Hands-on knowledge of Google ADK, Vertex AI, Gemini an d GCP services.

·         Experience with LangGraph, LangChain, AutoGen, CrewAI and microservices architecture.

·         Strong ability to define secure, scalable and governed production architectures.

RoleEngineer

Qualifications

BACHELOR OF TECHNOLOGY