Generative AI, VertexAI, Google ADK, AgenticAI, RAG Pipeline

Job description

**Virtual drive on 20th June.** **Generative AI, VertexAI, Google ADK, AgenticAI, RAG Pipeline** GenWe are looking for a skilled Generative AI Engineer to design, develop, and deploy enterprise-grade AI applications using Google Cloud technologies. The ideal candidate should have hands-on experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Vertex AI, Google Agent Development Kit (ADK), vector databases, and cloud-native AI architectures. Key Responsibilities Design and develop Generative AI solutions using Google Cloud Vertex AI. Build and deploy AI agents using Google ADK (Agent Development Kit). Develop and optimize Retrieval-Augmented Generation (RAG) pipelines for enterprise knowledge retrieval. Integrate LLMs such as Gemini, OpenAI, Claude, and open-source models. Create scalable prompt engineering and prompt management frameworks. Build document ingestion, chunking, embedding, indexing, and retrieval pipelines. Design multi-agent systems for workflow automation and intelligent decision-making. Implement vector databases and semantic search solutions. Develop APIs and microservices to integrate AI applications with enterprise systems. Monitor model performance, latency, costs, and AI quality metrics. Implement AI governance, security, and responsible AI practices. Collaborate with product, data engineering, and cloud teams to deliver AI-driven solutions. Required Skills Generative AI Large Language Models (LLMs) Prompt Engineering RAG Architecture AI Agents and Agentic Workflows Function Calling / Tool Use Fine-Tuning Concepts AI Evaluation Frameworks Google Cloud Vertex AI Gemini Models Vertex AI Agent Builder Vertex AI Search Vertex AI Pipelines Cloud Storage BigQuery Cloud Functions Cloud Run Agent Development Google Agent Development Kit (ADK) Multi-Agent Systems Agent Orchestration Tool Integration Workflow Automation RAG & Vector Search RAG Pipeline Design Embedding Models Document Chunking Strategies Semantic Search Vector Databases (Pinecone, Weaviate, ChromaDB, Vertex AI Vector Search) Knowledge Graph Concepts Programming Python FastAPI / Flask REST APIs LangChain LangGraph LlamaIndex SQL Cloud & DevOps Google Cloud Platform (GCP) Docker Kubernetes CI/CD Pipelines Git Infrastructure as Code Preferred Skills Experience with Gemini 2.x models. Knowledge of MCP (Model Context Protocol). Experience building conversational AI and enterprise copilots. Experience with document intelligence and OCR pipelines. Exposure to MLOps and LLMOps practices.