The opportunity

We are looking for an engineer who can work confidently inside Frappe/ERPNext and extend it with practical AI capabilities. The work spans operational automation, intelligent assistants, document and content workflows, recommendations, integrations, and data-enabled product features. We are not looking for prompt demos. The goal is secure, observable, testable software that people can depend on.

What you will build and own

- Frappe and ERPNext capabilities - Develop custom apps, DocTypes, workflows, reports, jobs, permissions, APIs, and maintainable extensions.
- AI-assisted workflows - Build assistants, retrieval workflows, classification, extraction, summarization, recommendation, and decision-support features.
- Reliable integrations - Connect ERP data with external services, internal platforms, data sources, and automation tools with clear contracts and failure handling.
- Production AI engineering - Implement evaluation, structured outputs, guardrails, human review, privacy controls, cost management, fallback behaviour, and monitoring.
- Data pipelines - Prepare, validate, transform, and synchronize operational data for AI and analytical use without compromising source-of-truth integrity.
- Experiment-to-product delivery - Prototype quickly, test with users, measure usefulness, then harden the right solution for production.
- Engineering quality - Write readable code, meaningful tests, migration scripts, documentation, and operational runbooks; participate actively in code review.

What we expect you to be good at





- Production development with Frappe Framework or ERPNext, supported by robust Python fundamentals.
- Building and consuming REST APIs, webhooks, background jobs, queues, and asynchronous workflows.
- Working with at least one major LLM platform and understanding tool/function calling, structured output, embeddings, retrieval, context limits, and model trade-offs.
- Evaluating AI behaviour with representative test cases rather than judging quality from a few impressive examples.
- Designing for hallucination risk, prompt injection, sensitive-data exposure, latency, rate limits, model failure, and unpredictable cost.
- Debugging across application, framework, integration, and data layers instead of repeatedly regenerating code.
- Explaining what AI should automate, what requires human approval, and what should remain deterministic software.
- Using AI coding assistants productively while reviewing every output and retaining full ownership of the result.

Experience

- Typically 4+ years in software engineering, with meaningful production experience in Frappe/ERPNext or an equivalent Python business-application framework.
- At least one AI-enabled workflow or product feature deployed beyond a personal demo or hackathon.
- Evidence of integrating external systems and supporting what you shipped in production.
- A portfolio, code sample, technical case study, or clear walkthrough of past work is strongly preferred.

Pay: ₹1,000,000.00 - ₹1,300,000.00 per year

Work Location: Remote

📌 ERPNext & Applied AI Engineer (India)
🏢 Important Group
📍 India