Full Stack Development Intern (AI-Focused)

How the job actually works

Remote-First Culture

Work from anywhere, with flexible hours.

Learning & Development

Continuous learning and skill programmes.

Work-Life Balance

Flexible schedules and time off.

What happens after you write to us

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1

AI Telephonic Interview

A short screening call with our AI interviewer, on any phone, at a time that suits you.

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2

AI Video Interview

Role-specific questions answered on video, reviewed by our team.

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3

Interview / Technical Test

An interview with team members, or a practical test of your skills.

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4

Offer

Final decision and offer discussion.

Full Stack Development Intern (AI-Focused)

Engineering In-office / Hybrid 3-6 months Internship

Develop web applications integrating AI features for assessment and proctoring platforms. Learn modern frontend/backend technologies while working with LLM APIs and cloud services.

What you’ll do

• Build responsive UI components using React.js, Next.js, or Vue.js with TypeScript
• Develop backend APIs using Node.js, Python (FastAPI/Flask), integrating ChatGPT and Google Gemini
• Work with RESTful APIs and JSON for integrating OpenAI, Hugging Face, and Google AI services
• Implement prompt engineering and testing for AI-powered features
• Build simple AI agents using LangChain or LlamaIndex (preferred)
• Work with SQL databases (PostgreSQL) and NoSQL (MongoDB) for data storage
• Perform data cleaning and preparation for frontend display and AI processing
• Use Git/GitHub for version control and collaborative development
• Deploy applications on cloud platforms (AWS, Google Cloud, Azure)
• Write clear technical documentation and maintain code quality
• Learn about AI ethics, bias detection, and responsible AI practices

Required skills & technologies

• Frontend: Angular (required), React.js, HTML, CSS, JavaScript/TypeScript basics
• Backend: Node.js or Python (Flask/FastAPI)
• Understanding of core ML algorithms: regression, classification, clustering
• Generative AI & LLM basics: use cases, limitations
• Prompt engineering and prompt testing: tuning and chaining
• Ability to build simple AI agents with LangChain, LlamaIndex, or Semantic Kernel (preferred)
• Work with RESTful APIs and JSON (OpenAI, Hugging Face, Google)
• Data cleaning and preparation for training/inference
• Version control with Git/GitHub
• Clear written communication for documentation
• Awareness of AI ethics and bias in software development
• Database: MS SQL Server (required), SQL basics (PostgreSQL, MySQL)