We're hiring a Full Stack Automation Engineer who operates at the intersection of AI and production systems. You'll build, optimize, and scale AI-powered infrastructure across the full stack — from LLM pipelines and RAG systems to dashboards and background workers. This is a high-ownership role. You won't be handed tickets. You'll be handed problems and trusted to solve them. ### WHAT YOU'LL BUILD & SCALE ### AI Communication Pipelines - Classify inbound messages by category, intent, urgency, and tone - Generate contextual responses using enrichment data - Implement and tune human approval gates ### AI-Powered Sales Intelligence - Transform raw enrichment data into structured pre-call briefs - Generate backgrounds, pain hypotheses, talking points, and rapport hooks ### RAG System - Maintain and improve the vector database with embeddings - Implement markdown-aware chunking strategies - Build async ingestion workers and semantic search APIs ### Trend Intelligence Engine - Process RSS feeds, social media, video platforms, and search trends - Generate reports, forecasts, and content drafts - Run autonomously on scheduled jobs ### Content Quality Pipeline - Extend the multi-agent system (outline → audit → generate) - Maintain binary quality gates (PASS/FAIL with citations) - Support multiple content formats across the pipeline ### Automated Lead Qualification - Enrich leads with product data and market insights - Build AI scoring and qualification grading systems - Generate automated audit reports ### AI Executive Assistant - Build and maintain Slack-integrated operations - Automate scheduling workflows - Triage and respond to email autonomously - Build and improve AI pipelines for client performance insights - Improve RAG retrieval quality (re-ranking, chunking, hybrid search) - Add tool use / function calling for real-time data in LLM pipelines - Debug classification errors and improve model accuracy - Optimize LLM costs, latency, and performance - Build dashboards for AI metrics and usage monitoring - Add observability and tracing to AI pipelines - Expand content quality systems to new formats and use cases Required: - Production LLM experience — Claude or OpenAI deployed in real, live systems - RAG system experience — embeddings, retrieval, chunking, and context handling - 3+ years TypeScript / Node.js - 2-3 years building end-to-end production systems spanning backend services, AI pipelines, and frontend dashboards - Bachelor's degree in Computer Science - Strong React skills (component architecture, state management, performance) - PostgreSQL — queries, migrations, indexing, query optimisation - API integrations — REST, OAuth, webhooks - Linux server experience — SSH, log analysis, debugging, deployments - AWS Lambda, Terraform, and Docker experience - Available during Eastern Time business hours Strong Pluses: - Multi-agent LLM systems and orchestration - Anthropic Claude expertise (prompt engineering, tool use, system prompts) - Vector search and embeddings (pgvector, Pinecone, or similar) - Slack API and bot development - Ad platform APIs (Meta, Google, LinkedIn) - LLM observability — cost tracking, tracing, monitoring - AI-assisted dev tools (Cursor, Claude Code, etc.) WHAT WE OFFER - High-impact role with genuine ownership over systems that matter - Full time remote role - Work directly on one of the most advanced AI-native business platforms in the Amazon space - A team that moves fast, thinks big, and holds a high bar - PTO after successfully completed probationary period