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Nineleaps is seeking a Generative AI Python Engineer to design and build AI-powered applications leveraging LLMs, RAG, and Agentic AI on Google Cloud Platform. This hybrid, full-time role offers hands-on work with Python, REST APIs, vector databases, and modern AI frameworks.
The ideal candidate has 3-4 years of Python software development, strong backend skills, experience with Flask, SQL, and AI model integration, and a passion for Generative AI and scalable systems.
Job Title: Generative AI Python Engineer (GenAI Python Engineer) | Nineleaps | Bangalore / Hyderabad, India
Recruiting Company: Nineleaps
Job Location: Bangalore or Hyderabad, India
Job Type: Full-Time | Hybrid
Nineleaps is seeking a talented Generative AI Python Engineer to design and build next-generation AI-powered applications leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI frameworks. This role offers the opportunity to work on innovative AI solutions that transform business processes through intelligent automation, advanced analytics, and conversational AI technologies.
As a GenAI Python Engineer, you will be part of a forward-thinking engineering team focused on delivering cutting-edge Artificial Intelligence solutions. You will design, develop, and optimize AI-driven applications using Python, REST APIs, vector databases, and cloud-native technologies on Google Cloud Platform (GCP). The position requires hands-on experience integrating Large Language Models through APIs, implementing RAG architectures, and developing intelligent agents capable of autonomous task execution. You will collaborate closely with product teams, solution architects, and data engineers to create scalable, reliable, and high-performance AI systems. This is an exciting opportunity for professionals passionate about Generative AI, machine learning innovation, and emerging AI technologies.
Showcase real-world Generative AI projects that demonstrate RAG implementation, LLM integration, vector database usage, and Agentic AI workflows. Candidates who clearly quantify business impact, such as reduced response time, improved accuracy, increased automation, or production-scale AI deployments, will have a significant advantage during shortlisting and technical interviews.