Senior GenAI Engineer – Gemini

About The Role We are looking for a

Senior Gemini AI Developer with strong expertise in

Generative AI, Python, LLMs, RAG architectures, and Google Gemini to design and develop enterprise-grade AI applications. The ideal candidate should have hands-on experience building AI agents, integrating multiple LLM providers, and deploying scalable AI solutions on Azure and Google Cloud. This role requires someone who can work across the complete AI application lifecycle—from solution architecture and prompt engineering to production deployment and optimization. Key Responsibilities

• Design, develop, and deploy enterprise-scale Generative AI applications using Google Gemini, Azure OpenAI, and other leading LLMs.
• Build intelligent AI assistants and AI Agents using Azure AI Foundry, Azure AI Services, or similar orchestration frameworks.
• Develop scalable Retrieval-Augmented Generation (RAG) solutions using vector databases, embeddings, document processing, and semantic search.
• Build Python-based AI services, APIs, automation workflows, and data ingestion pipelines.
• Integrate AI models with enterprise applications using REST APIs, SDKs, and cloud services.
• Evaluate, integrate, and optimize multi-cloud AI capabilities across Azure AI and Google Vertex AI.
• Implement prompt engineering, grounding techniques, context management, and response optimization.
• Develop secure, scalable, and production-ready AI architectures with monitoring, logging, and performance optimization.
• Collaborate with product managers, architects, and engineering teams to translate business requirements into AI-powered solutions.
• Stay updated with the latest advancements in Generative AI, LLMs, AI Agents, and cloud AI services. Mandatory Skills
• 5–10 years of software development experience with strong AI/ML exposure.
• Hands-on experience with Google Gemini APIs and Gemini-based application development.
• Strong proficiency in Python.
• Experience developing applications using Large Language Models (LLMs).
• Strong implementation experience with Retrieval-Augmented Generation (RAG).
• Experience with Azure AI Services and Azure AI Foundry.
• Experience building and managing AI Agents.
• Experience with Google Vertex AI and Gemini grounding.
• Strong understanding of cloud-native AI application architecture.
• Experience integrating REST APIs, SDKs, and enterprise applications.
• Excellent debugging, problem-solving, and analytical skills.

Preferred Skills

• Experience with LangChain, LangGraph, Semantic Kernel, LlamaIndex, or CrewAI.
• Knowledge of vector databases such as Pinecone, FAISS, ChromaDB, Azure AI Search, or Weaviate.
• Experience with prompt engineering, embeddings, semantic search, and document intelligence.
• Familiarity with Docker, Kubernetes, CI/CD pipelines, and cloud deployment.
• Experience with Azure Functions, App Services, or containerized AI deployments.
• Knowledge of AI governance, responsible AI, and security best practices. Technical Skills Mandatory
• Google Gemini
• Python
• Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• Azure AI Foundry
• Azure AI Services
• Google Vertex AI
• REST APIs Good to Have
• LangChain
• LangGraph
• Semantic Kernel
• LlamaIndex
• CrewAI
• Vector Databases
• Azure AI Search
• Pinecone
• ChromaDB
• FAISS
• Docker
• Kubernetes
• Git
• CI/CD
• Prompt Engineering

Experience

• 5–10 years of software development experience.
• Minimum 3+ years of hands-on experience in Generative AI or LLM application development.
• Proven experience delivering production-grade AI solutions. Skills: python,azure,gemini,cloud,google,agents,application,prompt