aimlroles

Automation AI Engineer

GigaBrands Open · verified Oct 22, 2026
Remote Brazil Mid-level AI Engineering

At a glance

Mid-level AI Engineering role at GigaBrands. Remote, Brazil.

Pay not stated AI Engineer salary

RoleAI Engineering
SeniorityMid-level
LocationBrazil
WorkplaceRemote
PostedMar 24, 2026 · 7mo ago
Role brief

aimlroles summary, based on the employer's posting.

What you'll do

  • Build pipelines that classify inbound messages, draft replies, and route them through human review
  • Turn lead and enrichment data into pre-call briefs, qualification scores, and audit reports
  • Improve retrieval in the RAG system and connect LLM pipelines to live data sources
  • Debug classification issues, lower model costs, and track AI performance with dashboards and observability
  • Extend content checks and scheduled trend reports across the platform’s AI workflows

What you bring

  • You have shipped LLMs such as Claude or OpenAI in production systems
  • You have built RAG systems using embeddings, retrieval, chunking, and context handling
  • You bring at least three years of TypeScript and Node.js work, plus strong React skills
  • You can work with PostgreSQL, API integrations, and Linux servers for debugging and deployments

Who this fits

This role suits a full-stack engineer who has built production AI systems and wants hands-on responsibility for pipelines, retrieval, and platform performance. It is remote and based in Brazil.

From the employer

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