AI Full Stack Engineer

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

Originally posted on Himalayas