Full Stack Automation Engineer
WHO WE ARE
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
OUR CORE VALUES
Be A Moral Human
Serve a higher purpose. Everything we build and every decision we make is grounded in doing the right thing.
Improve 1% Daily
Strive for 1% better every day. Consistent, compounding improvement is how we build world-class systems and teams.
Extreme Ownership
Own your actions. No excuses, no hand-offs as a crutch. If it's in your world, it's your responsibility.
Solve Problems, Don't Create Them
Every challenge has a solution. Don't slow down the team by creating new problems — come with answers, not blockers.
Make an Impact
Focus on meaningful results. We measure success by the difference we make, not the hours we log.
Fail Fast & Fail Forward
Don't be afraid to fail. Take that failure, learn from it, and move forward stronger. Every failure is a lesson.
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
Requirements
DAY-TO-DAY RESPONSIBILITIES
• 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
TECH STACK
Core: TypeScript · Node.js · React / Next.js · n8n · PostgreSQL · CI/CD · Claude Code
Nice to have: AWS Lambda · Terraform · Docker · Amazon SP-API · Slack Bots · Playwright
QUALIFICATIONS
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
• 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
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
• Amazon / eCommerce experience
• AI-assisted dev tools (Cursor, Claude Code, etc.)
WHAT WE OFFER
• Competitive salary based on experience
• 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
Benefits
WHAT WE OFFER
• Competitive salary based on experience
• 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
Skills
- AI
- Anthropic
- API
- AWS
- Backbone.js
- CI/CD
- Claude
- Claude Code
- Docker
- E-commerce
- Embeddings
- Lambda
- Linux
- LLM
- n8n
- Next.js
- Node.js
- OAuth
- Observability
- OpenAI
- pgvector
- Pinecone
- Playwright
- PostgreSQL
- Prompt Engineering
- React
- Semantic Search
- Slack
- SSH
- Terraform
- TypeScript
- Vector Databases
- Vector Search
- Webhooks
As published by workable · 7 questions · 1 written answer
Basics
First name, Last name, Email, Headline, Phone, Address, Photo, What is your desired monthly salary in American Dollars (USD)?, Education, Experience, Summary, Resume, Cover letter, Are you available to work from 9:00 AM to 6:00 PM EST?, Are you available to work full-time (40 hours per week)?, When could you start if hired?*
Pick from a list (6)
- Have you deployed a production LLM application (using Claude, OpenAI, or similar) that real users or systems actively rely on?
- Have you built or maintained a RAG system, including working with embeddings, chunking strategies, and semantic search?
- Do you have 3+ years of professional experience writing TypeScript and Node.js in a production environment?
- Are you comfortable taking ownership of open-ended problems without detailed task specifications or tickets — defining the solution yourself from a stated goal?
- Have you integrated external APIs (REST, OAuth, or webhooks) and debugged issues on a Linux server via SSH in a live production context?
- Have you completed Culture Index Survey? (candidates who didn't completed the survey , will not be considered in the next stages of hiring process)
Written answers (1)
- Copy this link to answer the Culture Index Survey, then paste the link of your result: https://go.cultureindex.com/p/yUYuNPFVO7slkanK