GigaBrands

Full Stack Automation Engineer

Remote, United States remote Entry Salary not listed
remote Technology & IT Curated
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About the role

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

Originally posted on Himalayas

Interview prep

Walk in with sharper answers.

Use this as a quick practice sheet before you speak with the employer.

Role
Technology & IT API integration Javascript MySQL Operations Remote Collaboration remote

Likely questions

  1. Tell us about work you have done that is close to the Full Stack Automation Engineer role.
  2. How would you approach your first 30 days at GigaBrands?
  3. Which of API integration, Javascript and MySQL have you used recently, and what did it help you achieve?
  4. Describe a time you solved a problem without waiting to be told exactly what to do.
  5. How do you stay organised and communicate clearly when working remotely?

Prepare before the call

  • A recent example that proves your experience with API integration, Javascript and MySQL.
  • One short story with a problem, your action, and the result.
  • Two examples that show the strengths listed on your CV.
  • A clear reason why this role and company interest you.
  • Your availability, preferred work style, and salary expectations.

Ask them

  • What would success look like in the first 90 days?
  • What are the main problems this hire should help solve?
  • How does the team give feedback and measure good work?
  • What does a normal working week look like for this role?
Practice line

I am interested in the Full Stack Automation Engineer role because I can bring practical experience in API integration, Javascript and MySQL, learn the team quickly, and contribute to the outcomes GigaBrands needs from this hire.

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