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AI Full Stack Engineer

Added 18 days ago

AI Full Stack Engineer

We’ve built an AI-native internal platform that powers every aspect of our Amazon brand management business. AI isn’t a feature — it’s the backbone.

  • LLMs classify and respond to inbound communications
  • AI generates pre-call intelligence briefs from raw enrichment data
  • A RAG system feeds context into every generation pipeline
  • An AI checkpoint system audits all generated content against quality gates

The platform is already live and scaling fast:

  • 17+ background services
  • 130+ frontend pages
  • 214 backend services
  • 184 database tables
  • Dozens of autonomous AI pipelines

We’re hiring an engineer who operates at the intersection of AI and production systems. You’ll build, optimize, and scale AI-powered infrastructure across the full stack.

What You’ll Build & Scale

AI Communication Pipelines

  • Classify inbound messages by category, intent, urgency, and tone
  • Generate contextual responses using enrichment data
  • Implement human approval gates

AI-Powered Sales Intelligence

  • Transform raw enrichment data into structured pre-call briefs
  • Generate: background, pain hypotheses, talking points, rapport hooks

RAG System

  • Vector database with embeddings
  • Markdown-aware chunking
  • Async ingestion workers
  • Semantic search API

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

  • Multi-agent system (outline → audit → generate)
  • Binary quality gates (PASS/FAIL with citations)
  • Supports multiple content formats

Automated Lead Qualification

  • Enrich leads with product data and market insights
  • AI scoring and qualification grading
  • Automated audit reports

AI Executive Assistant

  • Slack operations
  • Scheduling workflows
  • Email triage and follow-ups

Key Responsibilities

  • Build AI pipelines for client performance insights
  • Improve RAG retrieval quality
  • Add tool use for real-time data in LLM pipelines
  • Debug classification errors in AI systems
  • Optimize LLM costs and performance
  • Build dashboards for AI metrics and usage
  • Add observability to pipelines
  • Expand content quality systems

Qualifications

  • Production LLM experience (Claude/OpenAI in real systems)
  • RAG system experience (embeddings, retrieval, chunking, context handling)
  • 3+ years TypeScript / Node.js
  • Strong React skills
  • PostgreSQL (queries, migrations, indexing)
  • API integrations (REST, OAuth, webhooks)
  • Linux server experience (SSH, logs, debugging, deployments)

Strong Pluses

  • Multi-agent LLM systems

  • Anthropic Claude expertise

  • Vector search / embeddings

  • Slack API experience

  • Ad platform APIs (Meta, Google, LinkedIn)

  • LLM observability (cost, tracing, monitoring)

  • Amazon / eCommerce experience

  • AI-assisted dev tools (Cursor, Claude Code, etc.)

  • Competitive salary based on experience

  • High-impact role with strong ownership

  • Opportunity to scale cutting-edge AI systems to world-class level