Full Stack Automation Engineer
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 1d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 67d ago
The date the source published, not the day we noticed it (2026-07-10). Last seen at its source 1h ago.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
Brazil, Colombia
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay $90k–150k/yr
Middle 50% of 21 listings that do state pay — Engineering · all levels · Brazil · USD/year. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
workable employer's own board first seen 19d ago · last seen 1h ago
The listing
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