Gen AI Engineer
Job Title: Generative AI Developer
Experience: 3-5 Years
Location: Hybrid/Hyderabad
Employment Type: Full-time
Job Summary
We are seeking a Generative AI Developer with strong expertise in Azure and modern LLM ecosystems. The candidate will be responsible for building scalable, production-ready GenAI applications using Retrieval-Augmented Generation (RAG), LLMs, and multi-model integrations (including Claude and Gemini). This role requires hands-on coding experience and deep understanding of end-to-end AI solution development.
Key Responsibilities
Design and develop Generative AI solutions using Azure AI services and LLMs Build and implement RAG pipelines integrating vector databases and knowledge sources
Develop and optimize prompt engineering strategies across multiple LLMs (Claude, Gemini, etc.)
Integrate and orchestrate LLM-based applications using MCP (Model Context Protocol) Develop backend services and APIs using Python
Work with Azure OpenAI, Azure AI Studio, and Azure Machine Learning for deployment and scaling
Ensure performance, security, and cost optimization of AI solutions
Collaborate with cross-functional teams to translate business requirements into AI solutions
Evaluate and compare outputs across different LLM providers and optimize accordingly
Mandatory Skills
Strong programming skills in Python
Hands-on experience with Retrieval-Augmented Generation (RAG) Solid experience with Azure AI ecosystem (Azure OpenAI, Azure ML, AI Studio) Practical experience working with Large Language Models (LLMs) Experience with Claude (Anthropic) and Gemini (Google) models
Knowledge or experience with MCP (Model Context Protocol) for LLM orchestration and integrations
Experience in building and deploying scalable AI/ML applications
Required Skills & Qualifications
3-5 years of experience in AI/ML, software development, or related field Experience with NLP, prompt engineering, and LLM fine-tuning or adaptation Familiarity with vector databases (FAISS, Pinecone, or Azure Cognitive Search) Experience building REST APIs and microservices