Python LLM + Gen Ai Developer

Job description

We are seeking a skilled **Python LLM / Generative AI Developer** to design, develop, and deploy AI-powered applications leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and modern GenAI frameworks. You will contribute to feature development, optimize model performance, integrate AI capabilities into enterprise applications, and collaborate with cross-functional teams to deliver innovative AI solutions. - Design and develop production-grade Generative AI applications using Python and Large Language Models (LLMs). - Build and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases and enterprise knowledge sources. - Develop intelligent AI solutions leveraging frameworks such as LangChain, LlamaIndex, Semantic Kernel, and Azure OpenAI. - Integrate external APIs, enterprise systems, and data sources to enhance AI-driven workflows. - Implement prompt engineering, model evaluation, and response optimization techniques to improve accuracy and relevance. - Develop scalable backend services and APIs to support GenAI applications in production environments. - Collaborate with product, engineering, and business teams to embed AI capabilities into enterprise workflows. - Contribute to code reviews, technical documentation, and engineering best practices. - Strong Python programming with hands-on experience in AI/ML and Generative AI frameworks. - Working knowledge of Large Language Models (LLMs), prompt engineering, and model fine-tuning techniques. - Practical experience with LangChain, LlamaIndex, Semantic Kernel, OpenAI, Azure OpenAI, or similar GenAI frameworks. - Experience with vector databases, embeddings, retrieval systems, and RAG architectures. - Understanding of responsible AI practices, model evaluation, guardrails, and AI governance. Good to Have - Exposure to MLOps/LLMOps practices including model versioning, experiment tracking, and deployment automation. - Knowledge of Docker, Kubernetes, CI/CD pipelines, and cloud-native application development. - Experience with cloud AI services on Azure, AWS, or GCP. - Familiarity with monitoring, observability, and performance optimization of AI applications in production.