Internship Details

Job Details

• Work Mode: On-site
• Internship Duration: 6 Months
• Openings: 1
• Role Type: Internship

Job Summary

As an LLM Developer (GenAI Python) Intern, you will work on real-world AI engineering projects involving LLMs, RAG systems, local model deployment, AI-powered ERP workflows, APIs, databases, and intelligent business applications. This is a highly hands-on role for someone who wants to go beyond simply calling an AI API and learn how production-grade GenAI systems are designed, integrated, secured, and deployed.

We are looking for a technically curious Python / GenAI Intern who wants to build practical AI systems. You will work with senior developers and AI engineers to develop AI-powered features that connect language models with enterprise applications and business data. Depending on your skills and project requirements, you may work with commercial LLM APIs, open-source/local models, RAG pipelines, vector databases, Odoo/ERP systems, Python backends, AI guardrails, and tool-based AI workflows.

You are not expected to know every technology listed below before joining. Strong Python fundamentals, problem-solving ability, curiosity, and the ability to learn independently are the most important requirements.

What Youll Do

Generative AI Development

• Build AI-powered features using commercial and open-source language models.
• Integrate LLMs into real-world business applications and workflows.
• Develop Python-based orchestration logic for LLM applications.
• Work with prompts, context management, structured outputs, tool calling, and model responses.
• Experiment with different models and approaches to improve quality, latency, reliability, and cost.
• Evaluate AI outputs and identify failure cases.

RAG Knowledge Systems

• Build and improve Retrieval-Augmented Generation (RAG) pipelines.
• Work with documents, structured data, and other enterprise knowledge sources.
• Implement document processing, chunking, embeddings, retrieval, and context construction.
• Work with vector databases such as FAISS, ChromaDB, Qdrant, or Pinecone.
• Evaluate retrieval quality and improve the relevance of generated responses.
• Build AI systems that can answer questions using private enterprise data.

Local LLMs AI Infrastructure

• Experiment with locally hosted open-source language models.
• Learn and work with tools such as Ollama, Hugging Face, or vLLM.
• Understand the basics of model inference, quantization, resource requirements, and latency.
• Compare local models with commercial APIs for different use cases.
• Help build privacy-focused AI solutions where sensitive enterprise data should remain within controlled environments.

Python Backend Engineering

• Develop clean, maintainable Python code.
• Build backend services and APIs supporting AI-powered applications.
• Work with databases and structured enterprise data.
• Debug, test, and optimize AI and backend workflows.
• Read and improve existing codebases.
• Write reusable components instead of building one-off scripts.

ERP Odoo Integration

• Integrate AI capabilities into Odoo and enterprise workflows.
• Work with Python-based Odoo modules and the Odoo ORM.
• Understand how AI systems interact with business models and relational databases.
• Work with PostgreSQL and enterprise data structures.
• Develop AI-powered utilities, assistants, and workflow automation inside ERP applications.

AI Safety Reliability

• Implement input and output validation for AI systems.
• Develop guardrails to reduce unsafe, irrelevant, or unauthorized model behavior.
• Explore rule-based and model-based validation approaches.
• Test AI systems against unexpected, adversarial, or problematic inputs.
• Help protect sensitive enterprise information from unintended exposure.
• Monitor AI workflows for reliability and consistency.

Required Skills

Must Have

• Strong understanding of Python fundamentals.
• Good understanding of Object-Oriented Programming.
• Strong problem-solving and debugging ability.
• Understanding of functions, modules, classes, exceptions, data structures, and APIs.
• Basic understanding of SQL and relational databases.
• Understanding of JSON and HTTP/API concepts.
• Ability to read technical documentation and learn independently.
• Good communication and teamwork skills.
• Genuine interest and understadning in Generative AI and modern AI technologies.

Good to Have

Experience or familiarity with any of the following will be an advantage:

• OpenAI, Anthropic, Gemini, or other LLM APIs
• Hugging Face
• Ollama
• vLLM
• LangChain or similar frameworks
• RAG architecture
• Embeddings and vector search
• FAISS, ChromaDB, Qdrant, or Pinecone
• Odoo development
• Odoo ORM
• PostgreSQL
• REST APIs
• Docker
• Linux
• Git/GitHub
• Prompt engineering
• AI agents and tool calling
• LLM evaluation
• AI guardrails
• Model quantization
• Local LLM deployment

You do not need to know all of these technologies. Strong Python fundamentals and the ability to learn quickly are more important.

Who Were Looking For

You may be a good fit if you:

• Enjoy understanding how AI systems actually work.
• Like experimenting with new models, tools, and approaches.
• Can go through documentation, GitHub repositories, and technical articles to solve problems.
• Are comfortable debugging when things dont work as expected.
• Prefer understanding the underlying technology instead of blindly depending on frameworks.
• Are interested in both AI and backend/software engineering.
• Can work independently while knowing when to ask for help.
• Care about security, privacy, reliability, and correctness.
• Are excited about applying AI to real business problems

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.