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GigaBrands Himalayas · Posted yesterday

Full Stack Automation Engineer

Full time Remote

AI ML Engineering Automation Engineering Backend Development Software Engineering
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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

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