Job Description
We are seeking a Generative AI Solution Architect to lead the design and architecture of end-to-end Generative AI and multi-agent systems. This role is responsible for building scalable secure and production-grade GenAI solutions leveraging components such as RAG pipelines LLM Gateways and agent architectures. The GenAI SA ensures best-practice implementation including A2A interoperability and the use of Vertex AI Agent Builder / ADK on Google Cloud.
Key Responsibilities
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Architect end-to-end Generative AI solutions including RAG pipelines LLM Gateways vector stores and agent-based architectures.
-
Design secure scalable and interoperable multi-agent systems following A2A (Agent-to-Agent) principles.
-
Leverage Vertex AI including Agent Builder ADK Model Garden and orchestration frameworks.
-
Define architecture patterns for prompt engineering grounding tool integrations and LLM operations.
-
Ensure compliance performance observability and governance across all GenAI components.
-
Collaborate across ML data engineering application engineering and security teams to deliver enterprise-grade GenAI platforms.
-
Establish best practices for evaluation monitoring safety and responsible AI in agentic systems.
Required Skills
-
Strong experience architecting Generative AI and RAG-based solutions.
-
Deep understanding of LLMs embeddings vector databases and retrieval optimization patterns.
-
Hands-on experience with GCPs Vertex AI (Agent Builder ADK vector search LLM ops).
-
Knowledge of multi-agent frameworks orchestration patterns and tool/skill integrations.
-
Expertise in Python and modern AI/ML frameworks (LangChain LangGraph LlamaIndex etc.).
-
Strong understanding of security scalability and compliance for AI systems.
Preferred
Job Description We are seeking a Generative AI Solution Architect to lead the design and architecture of end-to-end Generative AI and multi-agent systems. This role is responsible for building scalable secure and production-grade GenAI solutions leveraging components such as RAG pipelines LLM Gatewa...
Job Description
We are seeking a Generative AI Solution Architect to lead the design and architecture of end-to-end Generative AI and multi-agent systems. This role is responsible for building scalable secure and production-grade GenAI solutions leveraging components such as RAG pipelines LLM Gateways and agent architectures. The GenAI SA ensures best-practice implementation including A2A interoperability and the use of Vertex AI Agent Builder / ADK on Google Cloud.
Key Responsibilities
-
Architect end-to-end Generative AI solutions including RAG pipelines LLM Gateways vector stores and agent-based architectures.
-
Design secure scalable and interoperable multi-agent systems following A2A (Agent-to-Agent) principles.
-
Leverage Vertex AI including Agent Builder ADK Model Garden and orchestration frameworks.
-
Define architecture patterns for prompt engineering grounding tool integrations and LLM operations.
-
Ensure compliance performance observability and governance across all GenAI components.
-
Collaborate across ML data engineering application engineering and security teams to deliver enterprise-grade GenAI platforms.
-
Establish best practices for evaluation monitoring safety and responsible AI in agentic systems.
Required Skills
-
Strong experience architecting Generative AI and RAG-based solutions.
-
Deep understanding of LLMs embeddings vector databases and retrieval optimization patterns.
-
Hands-on experience with GCPs Vertex AI (Agent Builder ADK vector search LLM ops).
-
Knowledge of multi-agent frameworks orchestration patterns and tool/skill integrations.
-
Expertise in Python and modern AI/ML frameworks (LangChain LangGraph LlamaIndex etc.).
-
Strong understanding of security scalability and compliance for AI systems.
Preferred
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