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Onsite or remote • Hubli+1💼 Internship🗓 2026-06-25

Core

Building grounded AI agents for Shopify brands to provide accurate answers on products, orders, policies, and shipping.

Role type

AI Engineer Intern (LLM + RAG)

Builds

RAG pipelines, product recommendation agents, order/shipping agents, omnichannel agents

Domain

E-commerce, AI, LLMs, RAG

Deliverable

production ML models

Required skills

LLMs, RAG, Python, Node.js, reasoning, debugging, APIs, JSON structured outputs

Preferred skills

experience building LLM/RAG projects

Technologies

Python, Node.js

Responsibilities

Build RAG pipelines, reduce hallucinations, improve relevance, create evaluation datasets, add guardrails, work with backend and product teams

Seniority

Intern

Rewrite
## About the role HelioAI (helioai.tech) is building a safe + controllable AI concierge for Shopify brands. Not random "text generation" we build grounded agents that give correct answers about products, orders, policies, shipping, refunds, etc. We're hiring an AI Engineer (LLM + RAG) who enjoys solving real reliability problems in production AI. College freshers with a fresh mind are welcome too. If you've built any LLM/RAG project and can learn fast. ## What you'll do - Build RAG pipelines (retrieval → grounded answers → citations) - Reduce hallucinations using structured outputs + tool calling - Improve relevance (chunking, embeddings, reranking, filters) - Create evaluation datasets + quality scoring (good/bad answers) - Add guardrails (policy-safe, brand-safe, deterministic for orders) - Work with backend + product to ship weekly improvements ## What you'll work on (examples) - Product recommendation agent (upsell + bundles + AOV lift) - Order + shipping agent (accurate, deterministic answers) - Knowledge updates (FAQs, policies, announcements) - Omnichannel agents (Web + WhatsApp + Instagram DM) ## Skills we're looking for - Strong basics in LLMs + RAG concepts - Python or Node.js (either is fine) - Reasoning + debugging mindset - Comfortable with APIs + JSON structured outputs ## Send Resume + GitHub + 2 projects you've built to https://www.linkedin.com/in/prkskrs/
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