AI Engineer Intern - AI Startup - Onsite HCMC only

Location HCMC onsite, Able to commit to 4-5 days/week for a 3–6 month internship.

ABOUT US

• We are an AI-powered Workforce Development Platform that enables Personalized Upskilling & Reskilling, hands-on Job Simulation, and Job Placement to create impactful outcomes for talents and employers.
• Our vision is to create a universe where everyone has the opportunity to unlock their full potential and thrive in the Future of Work.
• Our mission is to bridge the gap between traditional learning and employment through AI-powered upskilling and reskilling solutions.

At Edtronaut, AI isn’t just a feature — it’s the backbone of everything we do. From Job Simulations to AI-powered CV PowerUp and other AI products in the pipeline, we leverage AI to automate workflows, personalize upskilling, and reimagine how people prepare for their careers.

THE HIRING PROCESS

• Step 1: Submit your application/CVStep
• Step 2: Receive a short take-home case (you’ll have 3 days to complete) & submit your solutions
• Step 3: Final in-person interview to walk us through your thinking, approach, and learnings — plus mutual fit discussion
• Step 4: Decision & offer

SCOPE OF WORK

This isn’t your typical coffee-fetching, file-organizing internship. As our AI Engineer Intern, you will work closely with Product/BA, and SWE to bring our AI Job Simulation, CV PowerUp and other AI products across EdTech / HRTech in the pipeline to life. Your work will focus on AI Product Development, AI & Automation Workflow Development and other AI Ops including but not limited to research and experimenting with various AI models, API integrations and prompt engineering (with domain expertise required or Edtronaut’s support for development) to create intelligent, real-world learning scenarios in the most effective and cost efficient manner.

1. AI Automation & Workflow Integration

• Design and implement AI-powered automation pipelines to enhance Edtronaut’s internal and external processes — from data ingestion and user flow tracking to simulation content generation.
• Develop and maintain automated workflows using APIs, scripts, or orchestration tools (e.g., Python, Zapier, LangChain Agents, Airflow, or custom pipelines).
• Collaborate with Product and BA teams to identify opportunities for automation in the Job Simulation, CV PowerUp, and Job & Mentorship Matching modules.
• Build reusable automation scripts to connect AI APIs with internal databases, content repositories, or marketing workflows.
• Monitor and optimize pipeline performance for speed, scalability, and reliability.

2. AI API Integration & Model Exploration

• Research, test, and integrate AI APIs (OpenAI, Anthropic, Gemini, Mistral, etc.) into Edtronaut’s simulation and learning tools.
• Compare and evaluate model performance across tasks such as summarization, classification, and conversational agents.
• Design scalable, reusable functions for multi-model orchestration and response optimization.
• Collaborate with Back-End Engineers to develop and refine API endpoints and microservices for LLM-powered features.

3. Prompt Engineering & Simulation Building

• Craft, test, and refine prompts and instruction chains for Edtronaut’s AI Job Simulations, where users learn by solving workplace challenges using AI.
• Develop structured prompt templates that define task logic, feedback, and assessment rubrics.
• Work with Product and BA teams to simulate realistic work tasks (e.g., AI marketing assistant, product analyst, data reviewer).
• Optimize prompt reliability and accuracy across multiple contexts and user levels.

4. Prototyping & Feature Development

• Build proof-of-concept prototypes for AI-driven learning features (e.g., AI mentors, scenario simulators, auto-feedback modules).
• Design lightweight pipelines for inference and response evaluation, ensuring responsiveness and scalability.
• Collaborate on AI feature roadmaps with Product and Tech teams, contributing both technical and creative input.

5. Research & Continuous Learning

• Stay on top of the latest developments in different AI models, LLM prompting, multi-agent systems, and applied AI in education/workforce tech.
• Drive internal R&D sprints to test new tools, frameworks, or datasets.
• Present findings or mini-demos to the team as part of the AI Lab learning culture.

WHO ARE WE LOOKING FOR

*You’re a builder, problem-solver, and thinkerer who’s passionate about the inter…