Software Developer Intern

Technical duties

• Develop backend services and APIs using Python, Java, or GoLang.
• Build interactive and responsive user interfaces using React, Redux, Node.JS, JavaScript, AngularJS, HTML, and CSS.
• Implement generative AI application features utilizing LangChain, LangGraph, FastAPI, RAG, and MCP tools.
• Interact with and query databases including PostgresDB, MySQL, and ChromeDB.
• Write and execute automated test scripts using testing tools like Jest, Cypress, and Codecept.
• Contribute to DevOps workflows and CI/CD automation using Ansible and Python.

Project responsibilities

• Developing scalable API-driven microservices and workflow automation interfaces for enterprise cloud platforms.
• Integrating retrieval-augmented generation (RAG) pipelines and generative AI features into existing software solutions.
• Automating testing and deployment pipelines using modern CI/CD practices and containerization tools.

A typical day (Karyvio’s outline for this kind of role — not an employer commitment)

• Attend daily stand-up meetings with the development team to align on sprint goals and task priorities.
• Write, test, and debug code across frontend and backend components using Python, Java, Go, or JavaScript frameworks.
• Contribute to AI integration tasks, working with LangChain, FastAPI, and vector databases under mentor guidance.
• Participate in code reviews, pull request evaluations, and GitHub repository management.
• Build, run, and maintain automated test scripts using tools like Jest, Cypress, or Ansible to ensure high code coverage.

Skills that matter, and why

• Python

  Used widely across backend services, automation tasks, and AI tool integrations.

  How to learn it: Build REST APIs using FastAPI and practice writing scripts for automation tasks.

• React

  Enables creation of responsive, component-based user interfaces for modern web applications.

  How to learn it: Master state management with Redux and build dynamic single-page web apps.

• Generative AI

  Core requirement for building advanced AI-driven workflow automation and retrieval-augmented generation apps.

  How to learn it: Explore frameworks like LangChain and LangGraph alongside vector databases like ChromeDB.

• PostgresDB

  Reliable relational database management system used for persistent data storage in enterprise apps.

  How to learn it: Learn complex SQL queries, indexing, and integration with backend services like Node.js or Python.

Preparation plan

1. Strengthen core coding skills in Python, Java, or Go by solving basic data structure and algorithm problems.
2. Build a sample full-stack web application incorporating a React frontend and a Node.js or FastAPI backend.
3. Incorporate an AI component into a personal project, such as a simple RAG pipeline using LangChain or querying a local database.
4. Practice writing unit tests and end-to-end tests using testing frameworks like Jest or Cypress.
5. Set up a basic CI/CD pipeline using GitHub Actions and containerize a small application using Docker.
6. Review Linux command-line operations and basic shell scripting to feel comfortable with Unix-like environments.

Project ideas to show you can do the job

Interview guidance

• Brush up on core programming fundamentals using Go, Java, or Python, focusing on clean code principles and basic scripting.
• Prepare to discuss full-stack web concepts, particularly how frontend frameworks like React or AngularJS interact with Node.js or Python backend APIs.
• Review foundational concepts in generative AI and retrieval-augmented generation (RAG) using tools like LangChain and FastAPI.
• Be ready to explain database query fundamentals, schema design for PostgresDB or MySQL, and basic source code control workflows using GitHub.
• Understand basic DevOps principles, CI/CD pipelines, and automated testing tools such as Jest, Cypress, or Ansible.