Job Overview
We are seeking a Full Stack AI Engineer Intern who is excited to work at the intersection of Generative AI and modern web development.
In this role, you will help build AI-powered enterprise products by developing React-based interfaces, scalable Python backends, and intelligent LLM-driven workflows.
This internship is designed for engineers who want hands-on experience building real-world AI applications, not just model prototypes.
You will collaborate directly with founders, product leaders, and AI engineers to build production-ready AI systems used by enterprise customers.
Additional Information of the Intern
| Company | Sparsa AI |
| Location | Remote |
| Internship Duration | 6 months |
| Salary | ₹ 20,000 – ₹ 50,000 /Month |
| Working Days | 5 Days |
| Internship Type | Work From Home |
| Qualification | Bachelor’s degree |
| Skill | Python, React.js and TypeScript |
| Knowledge | React, FastAPI, or similar frameworks |
Key Responsibilities
– Design and optimize prompts for LLM systems such as OpenAI, Anthropic, or open-source models
– Develop structured prompting workflows for reliable AI outputs
– Experiment with advanced techniques such as few-shot prompting and chain-of-thought reasoning
– Improve AI response accuracy and reasoning capabilities
– Build scalable backend services using Python and FastAPI
– Design APIs that manage AI inference workflows
– Implement asynchronous processing and background tasks
– Integrate external APIs and enterprise systems
– Develop responsive interfaces using React.js and TypeScript
– Implement real-time streaming UI for AI-generated responses
– Manage application state using Redux or Zustand
– Build dashboards for displaying structured AI outputs and enterprise data
Eligibility Criteria
– Strong fundamentals in JavaScript or Python
– Basic experience with React, FastAPI, or similar frameworks
– Interest in LLM applications and AI-powered products
– Ability to learn quickly in a fast-paced startup environment
What You Will Learn
– Developing enterprise-grade AI applications
– Working with LLMs and multi-agent systems
– Designing AI-powered enterprise integrations
– Building scalable full-stack architectures
– Shipping features in a high-growth startup environment
