G

GigaBrands

Full Stack Automation Engineer

Full-TimeUpdated on 10/15/2026
No salary listed
Mid
Remote in Brazil
Remote
Software EngineeringAI Application Engineering, Full-Stack Engineering

About the job

Requirements
  • Production experience deploying Claude or OpenAI in live systems.
  • Experience with retrieval-augmented generation systems, including embeddings, retrieval, chunking, and context handling.
  • At least 3 years of TypeScript and Node.js experience.
  • Strong React skills, including component architecture, state management, and performance.
  • Experience with PostgreSQL queries, migrations, indexing, and query optimization.
  • Experience with REST API integrations, OAuth, and webhooks.
  • Linux server experience, including SSH, log analysis, debugging, and deployments.
Responsibilities
  • 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 asynchronous ingestion workers and semantic search APIs.
  • Process RSS feeds, social media, video platforms, and search trends.
  • Generate reports, forecasts, and content drafts.
  • Run trend intelligence autonomously on scheduled jobs.
  • Extend the multi-agent system through outlining, auditing, and generation.
  • Maintain binary quality gates with pass/fail results and 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 retrieval-augmented generation retrieval quality through re-ranking, chunking, and hybrid search.
  • Add tool use and function calling for real-time data in large language model pipelines.
  • Debug classification errors and improve model accuracy.
  • Optimize large language model 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.
Desired Qualifications
  • Experience with multi-agent large language model systems and orchestration.
  • Expertise with Anthropic Claude, including prompt engineering, tool use, and system prompts.
  • Experience with vector search and embeddings, such as pgvector or Pinecone.
  • Slack API and bot development experience.
  • Experience with advertising platform APIs, including Meta, Google, and LinkedIn.
  • Large language model observability experience, including cost tracking, tracing, and monitoring.
  • Amazon or e-commerce experience.
  • Experience with AI-assisted development tools such as Cursor or Claude Code.
  • Experience with AWS Lambda, Terraform, Docker, Amazon SP-API, Slack bots, or Playwright.

About the company

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