Location: Remote (LatAm or US) Reports to: CEO Type: Full-time, builder-first Compensation: USD 8k - 10k Role Overview We’re looking for a VP of AI & GEO (Generative Engineering & Operations) to lead the design, execution, and scaling of our generative AI infrastructure. This person will own the full stack that powers our copilots — including voice interfaces, prompt pipelines, RAG systems, and real-time decision engines. This is not a research role. It’s a hands-on, builder-first leadership position for someone who thrives in speed, complexity, and technical clarity. works directly with the CEO to make our vision real — and scalable. Key Responsibilities Design and scale the full GEO stack: voice transcription (Whisper), LLM prompts (OpenAI), embeddings and context recall (Pinecone, Weaviate, etc.) Lead the implementation of retrieval-augmented generation (RAG) pipelines across our 5,000+ and soon 5M+ diagnostic cases Build tool-based agents for our copilots: from repair guidance to procurement to fleet actions Set up logging, monitoring, evaluation, and fallback systems to ensure fast and reliable inference Collaborate with product to shape user flows and real-world use cases for mechanics and fleet operators Mentor and grow the technical team around best practices in generative systems and AI-native ops Qualifications 7+ years of experience building backend or AI systems, with at least 2 years shipping GenAI products Deep hands-on experience with OpenAI, LangChain or LangGraph, Whisper, Pinecone or equivalent vector DBs Strong Python engineering fundamentals (FastAPI, Docker, async workflows) Experience shipping real-world AI products, not just prototypes or research Respect from technical peers — ideally with a visible GitHub, community presence, or open-source contributions Fluency in prompt design, evaluation, and cost/latency trade-offs Low-ego, high-output, clear communicator Fluency in both Spanish and English Bonus Built copilots or agent-based interfaces from scratch Experience in speech-to-text and voice generation (e.g., Eleven Labs) Familiar with the automotive, logistics, or field operations industry Experience leading technical teams or mentoring other engineers Preferred Technical Toolkit This role requires hands-on technical depth. While not all are mandatory, the ideal candidate will have experience across most of the following: Programming Languages Python (core): for pipeline development, agents, FastAPI, and LLM integration TypeScript / JavaScript: for real-time interfaces and voice assistant integration SQL / NoSQL (PostgreSQL, MongoDB): for structured and semi-structured data management Bash / Shell scripting: for automation, version control, and deployment   Speech and Audio Technologies Speech-to-text: Whisper Text-to-speech: ElevenLabs, Coqui, or equivalent Optional: speaker diarization or voice cloning tools for advanced personalization AI Modeling & Infrastructure LangChain / LangGraph: to orchestrate complex generative agent workflows OpenAI APIs (chat, embeddings, whisper, function calling) Vector databases: Pinecone, Weaviate, FAISS, or Qdrant Whisper: for accurate voice-to-text transcription Docker / Docker Compose: for containerization of models and microservices FastAPI / async frameworks: for high-performance copilot APIs Evaluation and Performance Monitoring Weights & Biases / MLflow: for experiment tracking and model performance Prometheus / Grafana / OpenTelemetry: for observability and reliable inference in production Ray / Dask (optional): for scalable orchestration of complex AI pipelines