Generative AI & Python Engineering Intern

Build LLM tools, vector search pipelines, and agentic integrations with our core artificial intelligence division.

Ahmedabad, Gujarat (Office/Hybrid)

6 Months

hybrid

Monthly Stipend & PPO Benchmark₹15,000 – 25,000/moIncludes direct Pre-Placement Offer (PPO) opportunity, 1-on-1 mentorship, and production code deployment.

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Role Overview & Mission

Are you passionate about building real-world software powered by artificial intelligence? In this internship, you will work alongside our AI Solutions Architects to build production RAG agents, ingest multi-format datasets, and evaluate open-source foundation models.

Key Responsibilities & Deliverables

Develop Python microservices using FastAPI, LangChain, and vector embeddings.
Build document parsing pipelines for complex PDFs, spreadsheets, and web sources.
Assist in evaluating model accuracy, prompt optimization, and synthetic dataset generation.
Collaborate with frontend teams to connect AI backend microservices to reactive UI surfaces.

Prerequisites & Eligibility

Enrolled in Computer Science, Data Science, AI/ML, or related engineering degree (graduating 2025, 2026, 2027).
Strong programming proficiency in Python with good understanding of OOP and async patterns.
Familiarity with modern AI concepts (embeddings, RAG, prompt engineering, vector stores).
Strong mathematical and problem-solving aptitude.

Bonus Qualifications

Nice-to-Have Background

Experience with Hugging Face transformers, PyTorch, or OpenAI/Anthropic APIs.
Prior projects featuring LLM applications or retrieval systems.

Technologies & Architecture Tools

PythonFastAPILangChainVector DBPyTorchREST APIsGit

Perks & Engineering Culture

Generous monthly stipend (₹15,000 – ₹25,000 / month)

PPO opportunity for high performers to join our AI Engineering division

GPU cloud compute resources for research and exploration

Mentorship from experienced machine learning engineers

Corporate certification and recommendation letter

Direct Application

Join This Squad

We review every candidate submission within 48 business hours.