AI Engineer

About the Role We are looking for a highly skilled GenAI Engineer with strong Python development experience to design, develop, and deploy AI-powered applications using Large Language Models (LLMs) and Generative AI frameworks . The ideal candidate should have hands-on experience building RAG-based solutions, AI agents, and scalable backend services for enterprise-grade applications. Key Responsibilities Design and develop Generative AI applications using Python . Build RAG (Retrieval-Augmented Generation) pipelines using vector databases and document processing frameworks. Integrate and optimize LLMs such as OpenAI, Azure OpenAI, Claude, Llama, Mistral, or Gemini . Develop AI agents and multi-agent workflows using frameworks such as LangChain, LangGraph, CrewAI, or AutoGen . Create and maintain REST APIs / FastAPI services for AI model integration. Implement prompt engineering, evaluation, and monitoring for LLM applications. Work with cloud platforms ( Azure / AWS / GCP ) for deployment and scaling. Collaborate with data engineers, architects, and business stakeholders to deliver AI-driven solutions. Ensure performance, security, observability, and reliability of AI applications. Required Skills 5 to 7 years of software development experience with Python . Strong expertise in Python frameworks such as FastAPI, Flask, or Django . Hands-on experience with Generative AI and LLM integration . Experience with LangChain / LangGraph / CrewAI / AutoGen . Knowledge of vector databases such as FAISS, Pinecone, Weaviate, Chroma, or Azure AI Search . Strong understanding of RAG architecture, embeddings, semantic search, and prompt engineering . Experience working with SQL / NoSQL databases . Familiarity with Docker, Git, CI/CD pipelines, and cloud-native deployments . Good understanding of software design patterns, APIs, and scalable distributed systems . Preferred Qualifications Experience with Azure OpenAI Service or AWS Bedrock . Exposure to multi-agent orchestration and autonomous workflows . Knowledge of MLOps / LLMOps tools for model evaluation and monitoring. Understanding of data pipelines, ETL processes, and enterprise integration patterns . Experience with Node.js for AI service integration is an added advantage. Bachelors or Master’s degree in Computer Science, Information Technology, Data Science, or a related field . Nice to Have Experience with Hugging Face Transformers and open-source LLMs. Exposure to knowledge graphs, document intelligence, or conversational AI platforms . Contributions to AI/ML open-source projects or published AI solutions. What We Offer Opportunity to work on cutting-edge GenAI and Agentic AI projects . Exposure to enterprise-scale AI transformation initiatives . Collaborative and innovation-driven work environment. Continuous learning opportunities in LLMs, AI Agents, and Cloud AI services .