# Automation AI Engineer

**Company:** [GigaBrands](http://jobs.workable.com/companies/5t7GyhhPa66dSQ7emPDYfk.md)
**Location:** Remote
**Workplace:** remote
**Department:** Information Technology

[Apply for this job](http://jobs.workable.com/view/37111952-a7e1-4ffe-8e72-3146eae8ae78)

## 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

## Requirements

### 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.)

## Benefits

-   Competitive salary based on experience
-   High-impact role with strong ownership
-   Opportunity to scale cutting-edge AI systems to world-class level