As a Software Engineer specializing in AI agentic applications, you'll join a forward-thinking team dedicated to building both customer-facing and internal-facing intelligent chatbots and workflows that push the boundaries of agentic technology. You'll work on cutting-edge projects involving Retrieval-Augmented Generation (RAG), vector databases, and agentic frameworks, using Python and Go as your primary tools.This role offers the opportunity to design and deploy scalable, real-world solutions while collaborating with a dedicated team of Engineers. Your work will be visible in the Tesla mobile app and tesla.com, and will even be heard over the phone (when customers call our voice agents). * Develop and implement AI agentic applications using Python and Go, leveraging modern agentic frameworks * Build and optimize Retrieval-Augmented Generation (RAG) systems for enhanced AI performance * Design and manage vector databases (e.g., pgvector, FAISS) for efficient data handling * Utilize agentic frameworks to create robust workflows for language models and agent coordination * Conduct evaluation of models to assess performance, accuracy, and reliability, iterating as needed * Perform prompt engineering and tuning to optimize large language model outputs for specific use cases * Write clean, maintainable, and well-documented code in Python and Go, adhering to industry standards * Collaborate with team members to define requirements and deliver production-ready solutions * Debug, troubleshoot, and enhance AI systems for scalability and reliability * Stay ahead of the curve by exploring advancements in AI and agentic technologies * Degree in Computer Science, Engineering, or a related field or equivalent experience * Strong proficiency in Python and Go, with proven experience in agentic frameworks * Hands-on experience with Retrieval-Augmented Generation (RAG) and vector database technologies * Knowledge of Agentic frameworks like LangChain and LangGraph for orchestrating AI workflows * Solid grasp of machine learning and natural language processing (NLP) principles * Strong understanding of data modeling and data architecture * Familiarity with data quality checks and validation processes * Exceptional problem-solving skills and meticulous attention to detail * Experience with streaming speech-to-text and text-to-speech technologies is a plus