About Us
Kotty is an end-to-end e-commerce powerhouse. We handle our own manufacturing, manage our own warehouse operations, and sell across multiple major e-commerce platforms. We are looking for a practical, solutions-driven engineer to bring intelligent automation to our physical and digital operations.
The Role
You will build, deploy, and maintain AI-powered applications that solve real, operational bottlenecks in the e-commerce manufacturing lifecycle. Instead of pure research, you will focus on applied AI—shipping tools that make our factory, warehouse, and sales channels faster and smarter.
What You'll Do :
- Build & Deploy: Create scalable apps leveraging OpenAI APIs and LLM tools to automate workflows (e.g., inventory forecasting, unstructured data parsing, or production planning).
- Full-Stack Development: Write clean, production-ready code using JavaScript (Node.js/React) for AI orchestration and for internal tools and B2B dashboards.
- Integrate: Connect AI services directly into our existing warehouse management systems, factory floor processes, and multi-platform e-commerce endpoints.
- Ship Reliably: Enforce strong software development practices, ensuring AI apps are tested, stable, and deliver measurable ROI.
Who You Are :
- Strong engineering background in JS and React/Node.js.
- Hands-on experience building and deploying solutions with LLMs and OpenAI APIs.
- A product mindset with strict attention to CI/CD, testing, and clean architecture.
- Bonus: Experience integrating with e-commerce storefronts, ERPs, or logistics APIs, or previous experience working in the manufacturing industry.
Pay: ₹600,000.00 - ₹720,000.00 per year
Benefits:
Ability to commute/relocate:
- Faridabad, Haryana (Faridabad, Faridabad District): Reliably commute or planning to relocate before starting work (Required)
Application Question(s):
- Notice Period
- Current CTC and Expected CTC
- Briefly: what have you built end-to-end, start to finish, that is live and used by real people?
- Our factory sends production updates as WhatsApp messages, photos of handwritten registers, and inconsistent Excel sheets. We want a daily production dashboard out of this. How would you approach it? What would you build first, and what would you deliberately not automate?
- Describe a situation where you would NOT use an LLM, even though it technically could do the job. Why?
- You have two weeks and one engineer (you). The business wants five AI features. How do you decide what to build, and how do you communicate the trade-off?
- An LLM feature you shipped starts producing wrong outputs in production, but only sometimes. Users notice before you do. Walk us through how you debug and fix this.
Experience:
- JavaScript: 1 year (Required)
Work Location: In person
