Posted 1mo ago

AI Full Stack Engineer

@ GigaBrands
Austin, Texas, United States
RemoteFull Time
Responsibilities:Build AI pipelines, Improve RAG retrieval quality, Add real-time data tooling in LLM pipelines
Requirements Summary:Develop, deploy, and scale AI-powered infra; build AI pipelines; optimize LLM costs and performance.
Technical Tools Mentioned:TypeScript, Node.js, React, PostgreSQL, Linux, REST, OAuth, LLM/AI tooling
Save
Mark Applied
Hide Job
Report & Hide
Job Description

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