Role & responsibilities

- Conversational AI Development: Assist in building, fine-tuning, and optimizing chatbots and conversational AI systems.

- LLM &
- RAG Integration:

Work hands-on with Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) frameworks to generate accurate, context-aware, and reliable responses.

- API Development &

- Integration:

Design, build, and integrate robust RESTful APIs to connect AI models and chatbot interfaces with external platforms and business systems.

- ERP Data Integration: Support workflows that connect AI solutions and data pipelines with enterprise resource planning (ERP) software to automate business processes and retrieve operational data.

- Data Processing &

- Analysis:

Perform data preprocessing, feature engineering, and Exploratory Data Analysis (EDA) to prepare and structure data for model training.

- Production &

- Engineering Support:

Support the development, testing, and integration of AI models into scalable production systems.

- Research &

- Experimentation:

Contribute to ongoing research and experimentation around generative AI, advanced LLM architectures, and retrieval mechanisms.

- Cross-Functional Collaboration: Collaborate closely across product, engineering, and design teams to align AI features with user experience and technical requirements.

- Documentation &

- Communication:

Maintain clear technical documentation and present project outcomes and insights to internal stakeholders.

Preferred candidate profile

- Educational Background:



Recent graduate or final-year student pursuing a degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.

- Core Technical Knowledge: Strong foundational understanding of machine learning, deep learning, and Natural Language Processing (NLP) concepts.

- Programming Proficiency: Robust proficiency in Python and practical familiarity with ML/DL libraries such as PyTorch, TensorFlow, or Scikit-learn.

- API &
- Backend Familiarity:

Understanding of backend development principles, web frameworks, and experience building or consuming RESTful APIs.

- Enterprise Systems Exposure (Plus): Familiarity or prior academic/project exposure to integrating applications with enterprise systems, databases, or ERP platforms.

- GenAI &

- Tooling Exposure:

Hands-on exposure or familiarity with chatbot frameworks, LLMs (e.g., OpenAI, Hugging Face Transformers), vector databases (e.g., FAISS, Pinecone, Weaviate), and RAG pipelines.

- Data Handling Skills: Familiarity with data manipulation and visualization tools including Pandas, Matplotlib, and Seaborn.

- Desirable Extras (Nice-to-Haves):

- Experience with LLM orchestration tools like LangChain or LlamaIndex.

- Prior practical experience through chatbot projects, AI hackathons, or open-source contributions.

- Familiarity with cloud environments (AWS, GCP, Azure) and basic MLOps workflows.

- A personal GitHub or project portfolio demonstrating applied AI/NLP capabilities.

📌 AI Intern (New Delhi)
🏢 Sowiz
📍 New Delhi