We're hiring a Full Stack Automation Engineer who operates at the intersection of AI and production systems. You'll build, optimize, and scale AI-powered infrastructure across the full stack — from LLM pipelines and RAG systems to dashboards and background workers. This is a high-ownership role. You won't be handed tickets. You'll be handed problems and trusted to solve them.

What You'll Build & Scale AI Communication Pipelines

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

AI-Powered Sales Intelligence

- Transform raw enrichment data into structured pre-call briefs
- Generate backgrounds, pain hypotheses, talking points, and rapport hooks

RAG System

- Maintain and improve the vector database with embeddings
- Implement markdown-aware chunking strategies
- Build async ingestion workers and semantic search APIs

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

- Extend the multi-agent system (outline → audit → generate)
- Maintain binary quality gates (PASS/FAIL with citations)
- Support multiple content formats across the pipeline

Automated Lead Qualification

- Enrich leads with product data and market insights
- Build AI scoring and qualification grading systems
- Generate automated audit reports

AI Executive Assistant

- Build and maintain Slack-integrated operations
- Automate scheduling workflows
- Triage and respond to email autonomously
- Build and improve AI pipelines for client performance insights
- Improve RAG retrieval quality (re-ranking, chunking, hybrid search)




- Add tool use / function calling for real-time data in LLM pipelines
- Debug classification errors and improve model accuracy
- Optimize LLM costs, latency, and performance
- Build dashboards for AI metrics and usage monitoring
- Add observability and tracing to AI pipelines
- Expand content quality systems to new formats and use cases

Requirements Required:

- Production LLM experience — Claude or OpenAI deployed in real, live systems
- RAG system experience — embeddings, retrieval, chunking, and context handling
- 3+ years TypeScript / Node.js
- 2-3 years building end-to-end production systems spanning backend services, AI pipelines, and frontend dashboards
- Bachelor's degree in Computer Science
- Strong React skills (component architecture, state management, performance)
- PostgreSQL — queries, migrations, indexing, query optimisation
- API integrations — REST, OAuth, webhooks
- Linux server experience — SSH, log analysis, debugging, deployments
- AWS Lambda, Terraform, and Docker experience
- Available during Eastern Time business hours

Strong Pluses:
- Multi-agent LLM systems and orchestration
- Anthropic Claude expertise (prompt engineering, tool use, system prompts)
- Vector search and embeddings (pgvector, Pinecone, or similar)
- Slack API and bot development
- Ad platform APIs (Meta, Google, LinkedIn)
- LLM observability — cost tracking, tracing, monitoring
- AI-assisted dev tools (Cursor, Claude Code, etc.)

Benefits WHAT WE OFFER

- High-impact role with genuine ownership over systems that matter
- Full time remote role
- Work directly on one of the most advanced AI-native business platforms in the Amazon space
- A team that moves fast, thinks big, and holds a high bar
- PTO after successfully completed probationary period

📌 Full Stack Automation Engineer (Colombia)
🏢 GigaBrands
📍 Colombia