Full Stack Automation Engineer

🕒 July 10

🌐 Brazil, Colombia – Remote

🇧🇷 Brazil – Remote 🇨🇴 Colombia – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 QA Automation Engineer

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GigaBrands

WebsiteLinkedInAll Job Openings

1 - 10 employees

Founded 2022

📣 Marketing

🤖 Artificial Intelligence

🤝 B2B

Marketing • Artificial Intelligence • B2B

GigaBrands is a neuromarketing and AI-powered marketing agency that specializes in advertising services, particularly on platforms like Amazon. With a focus on leveraging advanced neuromarketing techniques and artificial intelligence, GigaBrands aims to transform online engagement into customer conversions, helping businesses reach new heights in their marketing efforts.

📋 Description

• Build, optimize, and scale AI-powered infrastructure across the full stack • Classify inbound messages by category, intent, urgency, and tone • Generate contextual responses using enrichment data • Implement and tune human approval gates • Transform raw enrichment data into structured pre-call briefs • Generate backgrounds, pain hypotheses, talking points, and rapport hooks • Maintain and improve the vector database with embeddings • Implement markdown-aware chunking strategies • Build async ingestion workers and semantic search APIs • Process RSS feeds, social media, video platforms, and search trends • Generate reports, forecasts, and content drafts • Run autonomously on scheduled jobs • Extend the multi-agent system (outline → audit → generate) • Maintain binary quality gates (PASS/FAIL with citations) • Support multiple content formats across the pipeline • Enrich leads with product data and market insights • Build AI scoring and qualification grading systems • Generate automated audit reports • 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

• 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

• 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