AI Engineering Apprentice Program (Worldwide)

What is this Apprentice Program?

The LunarTech AI Engineering Apprentice Program is a structured, high-performance learning experience designed for aspiring AI engineers who want to build real-world intelligent systems — not just experiment with models.

This program integrates applied AI development with structured education through LunarTech Academy, combined with hands-on engineering work across LunarTech’s ecosystem. Apprentices contribute to AI-powered platforms in education, healthcare, construction, energy, telecommunications, and other industry applications developed through LunarTech Labs.

You will work alongside senior AI engineers, product leaders, and system architects to design, build, test, and deploy intelligent systems — including LLM-powered applications, AI agents, retrieval systems, and scalable AI infrastructure.

The program places strong emphasis on AI systems thinking, LLM architecture, agentic workflows, model evaluation, and production-grade AI deployment. Apprentices learn not only how models work, but how intelligent systems are designed, validated, optimized, and scaled in real industry environments.

This apprenticeship is built to shape engineers who understand both theory and production execution in modern AI ecosystems.

What You’ll Gain

• A LunarTech Academy Scholarship, providing daily structured education in AI, science, and advanced technologies
• Deep exposure to LLM architecture, agentic AI systems, and AI infrastructure design
• Hands-on experience building and deploying live AI-driven platforms and industry applications
• Direct mentorship from experienced AI engineers and system architects
• Exposure to cross-industry AI product development (education, healthcare, construction, energy, telecommunications)
• Practical experience with RAG pipelines, AI agents, vector databases, and model evaluation
• Experience working in real development sprints and technical review cycles
• Development of technical communication and public speaking skills
• Structured feedback and performance reviews to accelerate engineering growth
• A portfolio of real AI systems and deployed solutions

By the end of the program, you will understand how to architect, deploy, and maintain production-level AI systems, not just train isolated models.

Program Duration & Conditions

• Location: Armenia (Remote/Hybrid collaboration model)
• Duration: 6 or 12 months (depending on candidate background and experience level)
• Compensation: Unpaid apprenticeship
• Includes: LunarTech Academy Scholarship + structured mentorship
• Language Requirement: Minimum B1 English proficiency (international team across multiple nationalities and continents)
• Eligibility: Bachelor’s degree (completed or in progress) in Computer Science, Data Science, AI, or related field

This program is designed for disciplined, technically curious individuals who want to operate in an international, high-performance AI engineering environment.

Key Responsibilities

• Assist in building and deploying LLM-based applications and AI agents
• Implement and optimize RAG pipelines using frameworks such as LangChain, LlamaIndex, or similar tools
• Support model training, fine-tuning, and evaluation using PyTorch, TensorFlow, or equivalent frameworks
• Work with vector databases (e.g., Qdrant, FAISS, PostgreSQL, or similar systems)
• Contribute to containerized deployment workflows (Docker, Kubernetes)
• Perform data preprocessing, experimentation, analysis, and performance evaluation
• Write clean, modular, production-ready Python code
• Participate in architecture discussions, technical reviews, and daily engineering syncs
• Apply structured AI insights from LunarTech Academy to improve system performance and scalability

Required Skills & Qualifications

• Strong programming foundation in Python
• Solid understanding of machine learning, deep learning, and large language models
• Hands-on experience with AI/ML projects (academic, personal, or open-source)
• Familiarity with LLM tooling such as LangChain, LlamaIndex, or agent-based workflows
• Experience with ML frameworks (PyTorch, TensorFlow, or similar)
• Understanding of vector databases and retrieval systems
• Basic knowledge of Git, Linux environments, and version control workflows
• Strong grounding in statistics and ML evaluation metrics
• Strong analytical thinking and system-level problem-solving ability
• Minimum B1 level English proficiency (required for international collaboration)
• Self-driven mindset with the ability to work independently and in structured teams

We are looking for engineers who think structurally, experiment rigorously, and are ready to build intelligent systems that operate at real-world scale across industries.