AI Developer Intern

About the Role

We are building the next generation of financial automation and are looking for curious, driven graduates to join us as AI Developer Interns. This is a hands-on learning role where you'll work alongside senior engineers and consultants to build real LLM-powered systems. You'll get exposure to the full lifecycle of an AI product: from understanding a business problem, to building a working prototype, to seeing it used by real clients. This internship is designed to fast-track your growth into a full-stack AI engineer. You'll be mentored, you'll make mistakes, and you'll ship real code.

Key Responsibilities

• Design, prototype, and iterate on AI/ML models for real business problems – from framing the problem and selecting an approach to evaluating results against baselines.
• Learn to build RAG (Retrieval-Augmented Generation) pipelines under guidance, using tools like LangChain/LangGraph and vector databases.
• Build and experiment with LLM-based systems: prompt engineering, embeddings, retrieval pipelines (RAG), and fine-tuning workflows, with growing ownership as you demonstrate capability.
• Implement and train ML/DL models using frameworks such as TensorFlow, PyTorch, or scikit-learn, and be able to justify architecture and hyperparameter choices.
• Build and expose model functionality through APIs (Python/FastAPI).

Requirements & Tech Stack

• Pursuing or recently completed BE/BTech/MCA, AI/ML, Data Science, or a closely related engineering discipline, with strong academic fundamentals in data structures, algorithms, and probability/statistics.
• Enjoys coding and building things, not just studying theory.
• Comfortable working in a fast-paced, learning-oriented environment.
• Eager to research, experiment, and try things hands-on, with support from mentors.
• Curious about Generative AI, AI Agents, LLMs, Computer Vision, and SaaS platforms.
• Comfortable "vibe coding" with AI pair-programming tools (Claude, Cursor, Copilot, or similar) to move fast, while still understanding and owning the underlying logic.
• Genuine interest in AI/LLMs – coursework, personal projects, or self-study count.
• Strong problem-solving ability and willingness to learn new tools quickly.
• Good communication skills – comfortable asking questions and explaining your work.

Nice-to-Have

• Academic or personal projects involving LLMs, ChatGPT API, or similar.
• Competitive Programming: Candidates are invited to include verifiable credentials, ranks, or assessment scores from recognized platforms – such as LeetCode, CodeSignal, HackerRank, Codeforces, CodeChef, or Kaggle.
• Familiarity with FastAPI, Flask, or any Python web framework.
• Basic knowledge of Docker or cloud platforms (AWS/Azure).
• Frontend basics (HTML/CSS/JS, React) for building simple prototypes.

Required Skill Set

• Python (FastAPI)
• LLMs (LangGraph, LangChain, Pydantic)
• RAG and Vector Databases
• AWS and Azure
• Vibe coding
• PostgreSQL and MongoDB
• Docker and Kubernetes
• Langfuse/LangSmith for observability

Why This Role

• Real work, real impact: You’ll contribute to systems used by actual clients, not throwaway assignments.
• Steep learning curve: Work directly with experienced engineers and consultants who will mentor you.
• AI-first exposure: Get hands-on with RAG pipelines and agentic workflows – skills that are in high demand.
• Career runway: Strong performers will be considered for full-time AI/ML Engineer roles.
• Startup pace, structured mentorship: Move fast, ask questions, and grow quickly in a supportive team.