AI Engineer (GenAI | Agentic AI | LLMs) | 4+ YOE

Company Description Axionix Technologies is a global digital transformation solutions provider that collaborates with leading technology companies to drive impactful change. The organization partners with clients from design through operation, embedding innovation and agility into their digital initiatives. With deep domain expertise and a future-focused mindset, Axionix helps companies outsource their digital projects and build high-quality tech teams. Axionix’s brands include EduKit (LMS & ERP for

al institutions), PropCRM (CRM for real estate), Towing Master (urban towing SaaS), and Marketika (omnichannel communication platform). Role Description: We're looking for an AI Engineer who enjoys building AI products that go beyond chatbots. If you've built LLM-powered applications, AI agents, RAG systems, or automated workflows that solve real business problems, we'd like to talk to you.

: • Develop AI-powered applications using modern LLMs and Agentic AI frameworks. • Design and implement Retrieval-Augmented Generation (RAG) pipelines for enterprise knowledge systems. • Build intelligent AI agents capable of reasoning, tool usage, and workflow automation. • Integrate AI models with backend services, APIs, databases, and third-party applications. • Optimize prompts, context windows, embeddings, and retrieval quality for production use cases. • Deploy, monitor, and improve AI systems with a focus on latency, accuracy, and scalability. • Work closely with product and engineering teams to rapidly prototype and ship AI features.

: • 3+ years of experience in Python with strong backend development skills. • Hands-on experience building applications using OpenAI, Anthropic, Gemini, or open-source LLMs. • Strong understanding of Prompt Engineering, RAG, Vector Databases, and Embeddings. • Experience with AI orchestration frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, or similar. • Good knowledge of FastAPI, REST APIs, and SQL/NoSQL databases. • Experience with cloud platforms (AWS/Azure/GCP) and deploying AI applications. • Familiarity with Docker, Git, and CI/CD pipelines.