_{04th May, 2026}

About the job:
Title – Gemini Enterprise Roles (Engineer)
Start date: Immediate
Position Type: Full Time
Location: Ahmedabad or Pune
  
Job Description: Gemini Enterprise Engineer
  
Role Overview
We are seeking a Gemini Enterprise Engineer to build and scale production-grade AI applications leveraging Google Gemini and the Google Cloud AI ecosystem. This role focuses on developing agentic, multimodal, and context-aware systems that integrate deeply with enterprise workflows.
  
Key Responsibilities

• Configure enterprise data connectors (SharePoint Online, Jira, Confluence, Salesforce, ServiceNow, Box, etc.)
• Design and build applications using Gemini models via Vertex AI (text, code, multimodal capabilities)
• Implement Retrieval-Augmented Generation (RAG) using enterprise data sources and vector stores
• Build and deploy agents using Google Agent Development Kit (ADK), Langchain, langgraph , Vertex AI Agent Engine, cloud run and Gemini Enterprise agent registration.
• Develop agentic workflows using Gemini with tool use, function calling, and orchestration patterns.
• Implement inter-agent communication using A2A (Agent2Agent) protocol and MCP (Model Context Protocol) to enable cross-platform agent interoperability and external tool connectivity.
• Configure Model Armor templates.
• Integrate Gemini into enterprise systems (CRM, ERP, data platforms) via APIs and event-driven architectures
• Optimize prompts, grounding strategies, and context windows for accuracy and cost efficiency
• Build evaluation pipelines for hallucination detection, response quality, and safety
• Ensure secure and compliant usage of enterprise data within Gemini-powered applications

  
Required Skills & Experience

• Hands-on experience with Gemini models or similar LLMs in production environments.
• Hands-on experience with ADK and other agentic frameworks, A2A protocol, MCP, and connector configuration (prebuilt and custom) within Gemini Enterprise.
• Strong Python/Java/Go skills with API-driven development, strong Knowledge of discovery engine Apis
• Experience with Vertex AI, embeddings, vector databases, and RAG architectures
• Understanding multimodal AI (text, image, code) use cases.
• Familiarity with prompt engineering, grounding, and model tuning techniques.

  
Preferred Qualifications

• Experience with Google Cloud services (BigQuery, Cloud Run, GKE, Pub/Sub, Agent engine)
• Exposure to agentic AI frameworks and multi-step reasoning systems
• Experience building enterprise copilots, assistants, or automation systems

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