Junior AI Developer

About the role

In this role as a Junior AI Developer, you will build and maintain robust Python-based backend services that integrate LLMs, vector databases, and RAG pipelines into existing application landscapes. You will collaborate with senior engineers to deploy production‑ready AI solutions while ensuring code remains clean, secure, and well‑documented.

• As a junior AI developer, you will develop robust backend services (primarily in Python) to integrate LLMs, vector databases, and other AI components into existing application landscapes
• You will be in charge of writing clean, secure, and maintainable code following central code quality guidelines and architecture principles
• This role includes collaboration with Senior engineers on building out our Internal Developer Platform and utilizing given modules for infrastructure self‑service with terraform
• Key duties will include tasks related to designing, testing, and optimizing prompts for various Language Models (LLMs) to achieve high‑quality, reliable outputs for specific business use cases
• You will implement Retrieval‑Augmented Generation (RAG) pipelines, including document chunking, embedding generation, and vector search strategies
• The role will assist in the evaluation and tracking of AI model performance, ensuring adherence to our AI evaluation and testing frameworks
• You will be responsible for creating and training machine learning models and neural networks for tasks like computer vision, speech recognition, and data analysis
• Creationand maintenance of document technical decisions, API endpoints, and system architectures clearly will be part of your responsibilities
• As a junior AI developer, you will actively participating in code reviews, bringing a fresh perspective and a willingness to learn from feedback
• You will work alongside within data engineers, stakeholders, and project managers to identify business needs and drive AI solutions
• This role involved cleaning and preparing large datasets to train and fine‑tune models
• You stay updated on cutting‑edge AI technologies, tools, and industry trends to keep projects innovative

• 1+ years of experience - AI engineering, data science, or machine learning, ideally with data engineering expertise
• Strong programming skills in Python and familiarity with software design patterns, object‑oriented programming, and functional programming concepts
• Understanding of version control (Git), CI/CD concepts, and RESTful API development (e.g., using FastAPI or Flask or plumber)
• Foundational understanding of a typical GenAI stack (LLMs, Vector Databases, frameworks like Lang Chain)
• Familiarity with cloud platforms such as Amazon Web Services, Microsoft Azure, or Google Cloud
• Experience deploying AI solutions using Docker and Kubernetes
• Knowledge of database systems (SQL and No
  
  SQL)
• Familiarity with Data Engineering concepts (Data Lakes, ETL/ELT pipelines)
• Solid knowledge and practical experience in no‑code and automation tools like as Make, n8n and Airtable
• Basic knowledge in ML frameworks and cloud‑based AI platforms like Azure ML and Databricks
• Experience with AI frameworks like Tensor Flow, PyTorch, and tools for building AI systems
• First‑hand experience building a basic RAG application or deploying an open‑source model locally
• Knowledge of MLOps practices and CI/CD pipelines
• Ability to collaborate effectively with clients, team members, and cross‑functional teams
• You are naturally inquisitive about the latest AI papers, open‑source tools, and architectural paradigms. You don't just copy‑paste solutions; you seek to understand the why
• You understand that "AI prototypes" are easy, but "production‑ready AI" is hard. You value writing tests (Pytest), handling edge cases, managing…