Empowering teams to align, execute, and deliver—seamlessly

AI Engineer- Intern

₹10,000 – ₹15,000 • No equity
|Remote (
Everywhere
)
|1 year of exp
|Internship

Reposted: 7 months ago

Hires remotely in

Everywhere

Remote Work Policy

Remote only

Company Location

Bangalore Rural

Visa Sponsorship

Not Available

RelocationNot Allowed

Skills

Database and Systems Design

API

OCR

Database Management

Tesseract Ocr

Data Parsing

FastAPI

LLMs

Libraries: Langchain, LLama-Index, NumPy, Scikit-Learn, Pandas, Matplotlib, Seaborn,

LLM Frameworks (Langchain, Claude, LLamaIndex) RAG Technologies Embedding Models Vect

Flask, Gradio, Tensorflow, Keras, PyTorch, OpenCV, Keras_OCR, Keras_OCR, PIL, NLTK

RAGs, ChatGPT, Hugging Face, LangChain, LlamaIndex, Transformers, VectorDB

Lanchain

About the job

*About the Product *

We are building an AI-powered Accounts Receivable Automation Platform that connects Salesforce (contracts), Stripe (billing), and ERP systems (NetSuite, QuickBooks) to automate: 1.) Invoice Generation 2.) Collections & Aging 3.) Bank Reconciliation

Our backend powers the AI agent network, integrating financial systems, managing workflows, and enabling LLM-driven automation.

Role and Responsibilities:-

Design and Develop Backend Systems:- Build scalable, reliable backend services using Python (FastAPI, Pydantic, MongoDB, Postgres) to power our AI agents.
Build AI-Powered Agents:-Develop and improve AI agents for invoice generation, collections automation, and bank reconciliation.
Integrate with Financial Platforms:- Connect seamlessly with Salesforce (contracts), Stripe (billing), QuickBooks/NetSuite (ERP), and banking APIs.
Own Data Pipelines & APIs:- Architect, optimize, and maintain data ingestion, processing, and reconciliation pipelines.
Contribute to AI/ML Models:- Work with LLMs, NLP, and ML frameworks (PyTorch/TensorFlow) to enhance reconciliation, classification, and forecasting accuracy.
Ensure Scalability & Reliability:- Deploy and monitor services on Kubernetes/Docker, ensuring fault tolerance and performance at scale.

Requirement:-

Strong knowledge of API design, distributed systems, and data pipelines.
Hands-on experience with databases (SQL & NoSQL).
Familiarity with AI/ML frameworks (e.g., PyTorch, TensorFlow, LangChain, LlamaIndex).
Solid understanding of cloud-native development (Docker, Kubernetes).
Knowledge of LLM-based AI agents, NLP, or financial document parsing.