AI Developer Intern

Hello Recruiter; India; On-site; INR 201,000 - 335,000; Full time

Job summary

Hello Recruiter is building an AI-powered recruiting platform designed to automate and optimize every stage of hiring. Our system leverages modern AI technologies to help organizations evaluate candidates more efficiently, reduce hiring costs, and improve decision-making.

We are looking for an AI Software Intern based in India who is curious about how modern AI systems and agents work, and eager to learn how to evaluate, test, and improve them in real-world scenarios.

Qualifications

• Final semester student or recent graduate in Computer Science, IT, or related field
• Available for a full-time (40 hrs/week) 6-month internship
• Strong interest in AI, Generative AI, and LLM-based systems
• Basic proficiency in Python
• Familiarity with APIs and software testing concepts
• Strong analytical and problem-solving skills
• Good written communication and documentation ability

Responsibilities

• Execute test plans for AI systems powered by Large Language Models (LLMs)
• Test across multiple input types: text, documents, structured data, and voice
• Build and maintain test cases, evaluation datasets, and benchmark scenarios
• Evaluate outputs for accuracy, latency, hallucination, and reliability
• Identify edge cases, failure modes, and unexpected behaviors
• Document findings clearly, including reproducible test cases
• Collaborate with engineering teams to validate fixes
• Assist in improving evaluation workflows and QA processes

Skills

Generative AI

AI Quality Assurance

Python

REST APIs

Prompt Engineering

Documentation

Problem Solving

API Testing

Job description

Just a heads up — The interview process for this role may include AI-based interviews.

Department

Experience

0+ years

Skills

Generative AI

AI Quality Assurance

Python

REST APIs

Prompt Engineering

Documentation

Problem Solving

API Testing

Job Description

Hello Recruiter is building an AI-powered recruiting platform designed to automate and optimize every stage of hiring. Our system leverages modern AI technologies to help organizations evaluate candidates more efficiently, reduce hiring costs, and improve decision-making.

Role Overview

We are looking for an AI Software Intern based in India who is curious about how modern AI systems and agents work, and eager to learn how to evaluate, test, and improve them in real-world scenarios.

This is a hands-on, learning-focused role with mentorship, where you will work on testing and validating AI systems that process text, files, voice, and video inputs.

Key Responsibilities

Execute test plans for AI systems powered by Large Language Models (LLMs)

Test across multiple input types: text, documents, structured data, and voice

Build and maintain test cases, evaluation datasets, and benchmark scenarios

Evaluate outputs for accuracy, latency, hallucination, and reliability

Identify edge cases, failure modes, and unexpected behaviors

Document findings clearly, including reproducible test cases

Collaborate with engineering teams to validate fixes

Assist in improving evaluation workflows and QA processes

Required Qualifications

Final semester student or recent graduate (Computer Science, IT, or related field)

Available for a full-time (40 hrs/week) 6-month internship

Strong interest in AI, Generative AI, and LLM-based systems

Basic proficiency in Python

Familiarity with APIs and software testing concepts

Strong analytical and problem-solving skills

Good written communication and documentation ability

Nice to Have

Exposure to LLM APIs (e.g., OpenAI, Anthropic, Gemini)

Familiarity with agent frameworks (LangChain, AutoGen, CrewAI)

Understanding of AI evaluation concepts (e.g., test datasets, regression testing)

Personal or academic projects involving AI or automation

What You’ll Gain

Hands-on experience with production-grade AI systems

Exposure to multimodal AI (text, voice, and data workflows)

Practical experience in AI evaluation and testing methodologies

Mentorship and structured learning in modern AI systems