Automation AI Engineer

GigaBrands; Colombia; On-site; COP 90,000,000 - 150,000,000; Full time

Benefits offered by this job

Competitive salary

High-impact ownership

Opportunities to scale AI systems

Job summary

GigaBrands is hiring an AI Full Stack Engineer to build and scale AI-powered infrastructure across the full stack. You’ll work at the intersection of AI and production systems, delivering scalable AI pipelines, dashboards, and observability.

The role focuses on reducing costs while improving performance and quality across the platform. You’ll develop end-to-end AI features, from inbound message classification to pre-call intelligence briefs, integrating with data sources and ensuring robust

Qualifications

• 3+ years of hands-on experience with TypeScript/Node.js in production
• Strong React skills with modern frontend architectures
• PostgreSQL query optimization, migrations, indexing
• Experience building and optimizing LLM-based pipelines (RAG)
• Ability to add observability, cost controls, and monitoring for AI systems
• Experience with REST/OAuth/webhooks integrations
• Familiarity with Linux server environments and deployments

Responsibilities

• Build AI pipelines for client performance insights
• Improve RAG retrieval quality and data enrichment
• Add tool integrations 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 and lead qualification systems

Skills

TypeScript/Node.js

React

PostgreSQL

API integrations

Linux server operations

Production LLMs

RAG systems

Cost and performance optimization

Tools

REST APIs

OAuth

Webhooks

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
• 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