Junior Full Stack Automation Engineer

About the role

We're hiring a Junior 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 where you'll be handed problems, not tickets, and trusted to solve them.

Responsibilities

• 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
• AI Pipeline Improvements
  • 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)
  • 2+ 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 optimization)
  • 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

• High-impact role with genuine ownership over systems that matter
• Salary from $2,500 - $3,500
• 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