AI Python Developer (LLMs, RAG, Chatbots & AI Agents)

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AI Python Developer (LLMs, RAG, Chatbots & AI Agents)

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 modern Python development standards.
• Collaborate with product, design, and business teams to translate requirements into scalable AI solutions.

Required Skills & Experience

• 2–5 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.