Full Stack Automation Engineer

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