Full Stack Automation Engineer

Job Description

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

Requirements

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.)

Benefits

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