LLM Developer (Gen AI - Python) Internship

About the Company

Arihant AI builds AI-powered business solutions, enterprise software, ERP systems, automation platforms, and intelligent applications for organizations across different industries. Our engineering team works at the intersection of Generative AI, Python, ERP systems, automation, and enterprise data.

About the Role

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. 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.

Responsibilities

• 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, Object-Oriented Programming, problem-solving, and debugging ability.
  • Understanding of functions, modules, classes, exceptions, data structures, and APIs.
  • Basic understanding of SQL and relational databases, JSON, and HTTP/API concepts.
  • Ability to read technical documentation and learn independently.
  • Good communication and teamwork skills.
  • Genuine interest and understanding in Generative AI and modern AI technologies.
• Good to Have (Familiarity with any of the following is 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, Pinecone)
  • Odoo development, Odoo ORM, PostgreSQL
  • REST APIs, Docker, Linux, Git/GitHub
  • Prompt engineering, AI agents, tool calling, LLM evaluation, AI guardrails, Model quantization, Local LLM deployment.
  • Note: Strong Python fundamentals and the ability to learn quickly are more important.

What You'll Learn

During this 6-month internship, you will gain practical experience in:

• Large Language Model application development, LLM API integration, Open-source and local LLM deployment.
• Prompt and context engineering, RAG architecture, Embeddings, and vector databases.
• AI agents and tool calling, LLM evaluation and reliability, AI guardrails and security.
• Python backend development, REST APIs, PostgreSQL, and enterprise data.
• Odoo/ERP integration, AI-powered business automation.
• Git-based software development, Debugging, and production-oriented engineering.

Internship Details & Benefits

• Duration: 6 months
• Location: Ahmedabad, Gujarat, India (On-site)
• Work Mode: On-site
• Openings: 1
• Experience: Freshers and students/recent graduates with strong technical fundamentals are welcome to apply.
• Start Date: As mutually agreed.
• Mentorship: From experienced AI and software engineers.
• Exposure: Real-world GenAI projects, enterprise AI, commercial and open-source AI models, private enterprise data, ERP/business automation, prototype to production lifecycle.
• Certificates: Internship completion certificate, Letter of Recommendation (based on performance).
• Opportunity: Potential full-time opportunity based on performance and business requirements.