Junior Full Stack Automation Engineer

We're hiring a Junior Full Stack Automation Engineer who operates at the intersection of AI and production systems. You'll build, optimize, and scale AI-powered infrastructure across the full stack — from LLM pipelines and RAG systems to dashboards and background workers. This is a high-ownership role. You won't be handed tickets. You'll be handed problems and trusted to solve them.
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

- 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

Requirements
Required:

- Production LLM experience — Claude or OpenAI deployed in real, live systems

- RAG system experience — embeddings, retrieval, chunking, and context handling

- 2+ years TypeScript / Node.js

- 2-3 years building end-to-end production systems spanning backend services, AI pipelines, and frontend dashboards

- Bachelor's degree in Computer Science

- 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

- AWS Lambda, Terraform, and Docker experience

- Available during Eastern Time business hours

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

- AI-assisted dev tools (Cursor, Claude Code, etc.)

Benefits
WHAT WE OFFER

- High-impact role with genuine ownership over systems that matter

- Salary from $2,500 - $3,500

- 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