Business Services & Consulting • all cities, MN 24
Automation AI Engineer (24)
all cities, MN 24On-sitePosted 20 hours ago
Business Services & Consulting
About the Role
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.
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
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.
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
What You'll Do
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
