Junior AI Developer

About this role

About the role: - Develop AI-powered applications and integrations at Mallow Technologies as a junior developer - Work with large language models and build systems that connect them to external data and services - Create backend services, APIs and prototypes that showcase AI capabilities - Debug and improve AI systems by understanding model behavior and performance metrics What you'll work on: - API development and integration with LLM services from providers like OpenAI, Anthropic and Gemini - Implementing retrieval-augmented generation (RAG) pipelines and AI agent architectures - Building vector database solutions for semantic search and embeddings - Structuring outputs from language models and enabling tool calling for agents - Connecting language models to external systems using the Model Context Protocol - Rapid prototyping of AI applications with Streamlit or Gradio - Writing clean, maintainable Python code following software development best practices What we're looking for: - 0–1 year of experience; freshers welcome to apply - Degree in AI/Machine Learning, Computer Science or IT - Solid Python skills and understanding of backend development principles - Strong grasp of how language models work: tokenisation, context windows, embeddings, transformer architecture, temperature and sampling - Knowledge of fundamental API design, asynchronous programming and REST principles - Hands-on experience building with frameworks such as LangChain, LangGraph, CrewAI, AutoGen, LlamaIndex or OpenAI Agents SDK - Familiarity with vector databases including FAISS, ChromaDB and pgvector - Practical exposure to prompt engineering, RAG, and agent patterns like ReAct - Understanding of the Model Context Protocol, its tools, resources and application - Comfort with SQL, FastAPI or Flask, JSON and Git - At least one AI certification or completed online course - Completed AI projects from academics, internships, hackathons or personal work, with GitHub or portfolio evidence - Problem-solving ability and clear communication - Genuine enthusiasm for learning new tools and techniques Preferred qualifications: - Experience with LangSmith, Langfuse, Ragas or DeepEval for evaluation and tracing - Basic Docker knowledge and exposure to AWS, Azure or GCP - Familiarity with machine learning fundamentals, deep learning concepts or NLP basics including Precision, Recall and F1 Score - Work with Hugging Face and open-source language models - Knowledge of AI security considerations, OWASP Top 10 for LLM Applications, DPDP Act and GDPR - Proficiency using AI coding tools like Claude Code, Cursor and GitHub Copilot responsibly - Contributions to open-source projects