Associate AI Full Stack Engineer

Atlassian Intelligence; Pune District; On-site; INR 600,000 - 900,000; Full time

Job summary

Atlassian Intelligence in Pune is building GenAI-powered applications that integrate LLMs, retrieval systems and cloud-native infrastructure. We seek early-career engineers who grasp AI/NLP basics and full-stack development, and who are eager to grow into production-grade AI solutions.

You will collaborate with senior engineers, ship real features, and ramp up quickly, contributing to front-end with React and backend APIs in Node.js/Python, while deploying AI workloads on AWS.

Qualifications

• Proficiency in Python and AI/NLP fundamentals.

Responsibilities

• Assist in building RAG pipelines and LLM-powered features.

Skills

Python

NLP fundamentals

Text vectorization

Transformers

LLMs basics

RAG concepts

LangChain

React

Node.js

Git

SQL/NoSQL

AWS basics

Tools

FAISS

ChromaDB

LangChain

REST APIs

Job description

• Experience Level: 6 months-1 year
• Function: Engineering - AI / Full Stack Development
• No. of vacancies: 4

About the Role

We’re building GenAI-powered applications that combine large language models, retrieval systems, and cloud-native infrastructure. We’re looking for early-career engineers who have a strong grasp of AI/NLP fundamentals and full-stack development basics, and are eager to grow into building production-grade AI applications. You’ll work closely with senior engineers, ship real features, and ramp up fast.

What You’ll Do

• Assist in building and integrating RAG pipelines and LLM-powered features
• Develop front-end interfaces using React under guidance from senior engineers
• Build and maintain backend APIs using Node.js/Python
• Work with vector databases and LangChain for retrieval-based features
• Support deployment and testing of AI workloads on AWS
• Learn and follow team practices for code quality, version control, and testing
• Collaborate with product, design, and QA, and communicate progress/blockers clearly

Must-Have Skills

Programming & AI/NLP Fundamentals

• Proficiency in Python
• Understanding of NLP basics: tokenization, text preprocessing, POS tagging, NER
• Text vectorization concepts: BoW, TF-IDF, Word2Vec/embeddings – should be able to explain and implement
• Conceptual understanding of transformer architecture (self-attention, positional encoding)
• High-level understanding of how LLMs (GPT/LLaMA-class models) work
• Exposure to RAG concepts and vector databases (FAISS or ChromaDB) – academic or personal projects acceptable
• Basic hands-on experience with LangChain (document loaders, text splitters, simple chains)

Full Stack Development

• React fundamentals – components, props, state, hooks, JavaScript/TypeScript, HTML, CSS
• Node.js basics – building simple REST APIs
• Git – clone, commit, branch, pull requests
• Basic SQL/NoSQL – CRUD operations

Cloud (AWS) - Conceptual

• Conceptual awareness of Lambda, DynamoDB, and IAM – what they are and when they’re used

Soft Skills

• Strong communication – written and verbal
• Willingness to learn independently and ask the right questions
• Problem-solving attitude – takes initiative rather than waiting for exact instructions

Nice-to-Have

• A personal or academic RAG/chatbot project (end-to-end, however small)
• Exposure to MCP, LangGraph, or agentic frameworks
• Basic fine-tuning exposure (LoRA/QLoRA) via coursework or tutorials
• Self-learned, free-tier hands-on experience with AWS Bedrock or SageMaker
• Any exposure to Atlassian Forge, Bitbucket, or Jest/unit testing