Automation AI 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 3d 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 175d ago
The date the source published, not the day we noticed it (2026-03-24). Last seen at its source just now.
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, Pakistan, Philippines
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 just now
The listing
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