AI Developer (LLMs, RAG, Chatbots) (Chennai)

LOCATION: CHENNAI / HYBRID We are seeking a highly skilled AI Python Developer with hands-on experience in building production-grade applications powered by Large Language Models (LLMs). The ideal candidate should have a strong background in designing and deploying AI agents, chatbots, and Retrieval-Augmented Generation (RAG) systems, along with experience in integrating AI into real-world business workflows. Key Responsibilities - Design, develop, and deploy AI-powered applications including chatbots, AI agents, and automation workflows using modern LLMs. - Build and optimize RAG pipelines leveraging frameworks like LangChain, LlamaIndex, and vector databases. - Architect and implement scalable, cloud-native AI solutions using AWS (Lambda, EC2, S3, API Gateway, etc.). - Integrate AI solutions with CRM and SaaS platforms such as GoHighLevel, HubSpot, and other business tools. - Develop voice and conversational AI systems using platforms like Vapi, Twilio, ElevenLabs, or similar. - Implement prompt engineering, fine-tuning, and LLM orchestration strategies for performance and reliability. - Ensure code quality, scalability, and maintainability following up-to-date Python development standards. - Collaborate with product, design, and business teams to translate requirements into scalable AI solutions. Required Skills & Experience - 25 years of professional experience in Python development. - Strong hands-on experience with LLMs (GPT, Claude, Grok, DeepSeek, or similar). - Solid experience with RAG architectures, embeddings, vector search, and semantic retrieval. - Proficiency in LangChain, LlamaIndex, or similar AI frameworks. - Experience with vector databases (Pinecone, Weaviate, FAISS, etc.). - Strong understanding of prompt engineering, chaining, and agent-based workflows. - Experience with AWS cloud services and serverless architectures. - Hands-on experience building chatbots and/or voice agents. - Familiarity with API integrations and third-party SaaS ecosystems (CRM, marketing tools, etc.). - Good understanding of REST APIs, WebSockets, and backend architecture. Good to Have - Experience with fine-tuning or open-source LLMs. - Knowledge of Docker, CI/CD pipelines, and DevOps practices. - Exposure to real-time systems and streaming architectures. - Understanding of AI cost optimization and performance tuning. - Prior experience working in startup or product-based environments. .