About the role
·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.
Qualifications: BACHELOR OF TECHNOLOGY