Junior AI Developer

We are looking for a hands- on Junior AI Developer to join our team in building next- generation AI solutions. This role goes beyond simply running models on Google Colab — you will be directly involved in the end- to- end development lifecycle, from frontend interface development, backend logic implementation, and model optimization (RAG/Inference) to deployment packaging (Docker/Linux).
KEY RESPONSIBILITIES:

System Development: Build RAG (Retrieval- Augmented Generation) systems integrated with Vector Databases such as ChromaDB, Milvus, and Qdrant.
Open- source Contribution: Research, apply, and customize the latest open- source tools and frameworks from the global AI community.
Fullstack Lite: Develop user interfaces (Web UI) using HTML5, CSS3, JavaScript (or React/Streamlit) and integrate them with Python APIs built on FastAPI/Flask.
AI Implementation: Deploy and optimize open- source LLMs (such as Llama 3, Qwen, Mistral, etc.) using Ollama or vLLM on on- premise infrastructure.
Deployment: Package applications into Docker containers, and manage as well as operate systems in Linux/Ubuntu Server environments.

PROFESSIONAL REQUIREMENTS:
Programming & AI Skills:

Vector DB: Good understanding of embeddings and querying unstructured data.
Python: Strong proficiency in core Python, data processing, and API development.
AI Tools: Hands- on experience with LangChain or LlamaIndex. Solid understanding of Prompt Engineering.

Frontend & User Experience:

UI/UX: Basic aesthetic sense with the ability to design user- friendly and intuitive chatbot/dashboard interfaces.
Frontend: Strong knowledge of HTML5, CSS3, and JavaScript (ES6+). Familiarity with Tailwind CSS is an advantage.

Systems & Infrastructure:

OS: Proficient in using Linux command line tools (Bash scripting), with understanding of process management and permission control on Ubuntu/CentOS.
Open- source: Habit of reading technical documentation on GitHub and capable of troubleshooting installation issues related to open- source libraries.
Docker: Ability to write Dockerfiles and use Docker Compose to set up AI runtime environments, including application containers, databases, and inference engines.

ADDITIONAL REQUIREMENTS:

Having real- world projects on GitHub (please attach the GitHub link in your CV).
Experience in building a home lab or deploying AI solutions on personal machines/private servers.
Good English reading comprehension for technical documentation.

BENEFITS:

Hands- on working environment: Opportunity to work directly with high- performance GPU systems and AI projects for companies within the Sovico ecosystem, including HDBank, VikkiBank, VietJet Air, FinX, and others.
Open- source culture: Encouragement to contribute to the community and build your personal brand through open- source projects.
Unlimited learning opportunities: In- depth training on AI system architecture, from hardware to software.
Competitive salary and bonus package, with a clear career progression path toward Mid- level / Senior AI Engineer.

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Cập nhật gần nhất lúc: 2026-04-16 14:00:07