AI Engineer to Build a Personalized Finance Podcast Intelligence Assistant

AI Engineer to Build a Personalized Finance Podcast Intelligence Assistant We're looking for an experienced AI engineer to build a private system that turns long-form finance podcasts into concise, actionable investment insights. The goal is not simply summarization, we want an AI research assistant that understands recurring themes across dozens of podcasts and produces high-quality investment intelligence. Responsibilities Pull podcast episodes automatically (YouTube, Spotify, RSS) Transcribe audio using Whisper or similar Break transcripts into logical sections Use GPT-5 / Claude to summarize key ideas Extract: Investment theses Company mentions Macro themes Bull vs. bear arguments Actionable takeaways Risks Compare ideas across multiple podcasts Detect recurring themes over time Store everything in a searchable knowledge base (Notion or similar) Deliver a daily digest by email or Slack Nice-to-have Experience with: OpenAI API Claude API LangChain or LangGraph n8n Make.com Python Whisper Pinecone Weaviate Supabase Notion API Retrieval-Augmented Generation (RAG) MCP servers Agentic AI workflows End Goal The finished product should function like a personal investment research analyst. Example daily output: Top 5 ideas mentioned today Highest-conviction stock picks Consensus themes across podcasts New macro risks emerging Contrarian viewpoints Companies mentioned most frequently Actionable investment opportunities The system should become smarter over time by remembering previous episodes and connecting related ideas rather than treating every podcast independently.