AI Engineer- Intern
An intern role building backend services and AI agents for an AI-powered accounts receivable automation platform that connects Salesforce, Stripe, and ERP systems to automate invoicing, collections, and bank reconciliation. Day-to-day work centers on Python/FastAPI, MongoDB/Postgres, LLM-based agents, and Docker/Kubernetes deployments.
- Compensation
- ₹10K–₹15K
- Location
- Bangalore Rural
- Work setup
- Not specified
- Seniority
- Intern
- Employment
- Internship
- Experience
- Not specified
- Category
- Ai engineering
- Posted
Skills
Must have
- 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
Full description
Compensation: ₹10,000 – ₹15,000 • No equity
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.