AI Backend / Full-Stack Developer

AI Backend / Full-Stack Developer – Multilingual AI Assistant Platform

Location: Remote

Employment Type: Full-time / Contract

Experience: 3+ Years

Tech Stack: Node.js, TypeScript, LLMs, Qwen, PostgreSQL, Redis, React, Docker

About the Role

We are looking for an experienced AI Backend / Full-Stack Developer to build and scale a production-ready, multilingual AI assistant capable of understanding English, Hindi, and Hinglish and translating natural-language requests into secure application workflows.

The platform will support account management, wallet operations, payment workflows, transaction history, real-time information retrieval, application navigation, and customer support.

An initial Node.js implementation already includes intent classification, structured entity extraction, local Qwen3 inference, a testing interface, and automated tests.

You will extend this foundation into a reliable, scalable platform with authenticated API integrations, conversation management, secure transaction handling, monitoring, and production deployment.

This is a hands-on engineering role focused on developing, integrating, testing, and shipping production software.

Key Responsibilities

• Design, develop, and maintain scalable backend services using Node.js and TypeScript.
• Integrate self-hosted LLMs using OpenAI-compatible APIs or equivalent interfaces.
• Build multilingual intent recognition and entity extraction for English, Hindi, and Hinglish.
• Implement conversational context, clarification flows, and multi-step interactions.
• Integrate the AI assistant with account, wallet, payment, transaction, and customer support APIs.
• Develop a secure tool/function-calling framework with schema validation and deterministic business logic.
• Implement authentication, authorization, transaction confirmation, and audit logging.
• Handle API failures, retries, timeouts, idempotency, and duplicate requests.
• Build responsive conversational interfaces and internal management dashboards.
• Optimize model inference performance, response latency, and resource utilization.
• Develop automated evaluation pipelines for intent accuracy, entity extraction, and workflow completion.
• Write unit, integration, and end-to-end tests.
• Set up CI/CD pipelines, logging, monitoring, and production deployments.
• Collaborate with product, frontend, and backend teams to define API contracts and deliver features.

Required Skills

• 3+ years of software development experience, preferably in backend or full-stack development.
• Strong proficiency in JavaScript, TypeScript, and Node.js.
• Experience building and integrating REST APIs.
• Practical experience integrating LLMs into real-world applications.
• Understanding of structured LLM outputs, JSON Schema, function calling, and response validation.
• Experience with authentication, role-based access control, and secure API communication.
• Understanding of transactional workflows, state management, retries, and idempotency.
• Experience with PostgreSQL or similar relational databases.
• Familiarity with Redis for caching and session management.
• Working knowledge of Docker, Git, CI/CD, and Linux environments.
• Experience writing automated tests and debugging production applications.
• Ability to develop modular, maintainable, and well-documented code.
• Ability to work with Hindi and Hinglish inputs, including romanized Hindi and common abbreviations.

Good to Have

• Experience with Qwen, Llama, or other open-weight language models.
• Familiarity with LM Studio, Ollama, vLLM, or llama.cpp.
• Experience with React or Next.js.
• Experience integrating payment gateways, digital wallets, or financial APIs.
• Knowledge of WebSockets, Server-Sent Events (SSE), message queues, and asynchronous processing.
• Familiarity with prompt-injection prevention, sensitive-data redaction, and LLM observability.
• Experience optimizing GPU utilization, inference speed, and model-serving costs.
• Understanding of Retrieval-Augmented Generation (RAG).
• Experience deploying and operating self-hosted AI services.

What You'll Work On

• AI & Natural Language Understanding

Improve multilingual intent recognition, entity extraction, conversational context, and structured LLM responses.

• Backend & API Integrations

Connect AI-generated intents to authenticated application APIs with strong validation, permission checks, and error handling.

• Conversational Workflows

Build multi-step conversations, clarification mechanisms, user confirmations, and reliable workflow execution.

• AI Model Integration & Optimization

Integrate and optimize self-hosted models, improve inference performance, and establish evaluation benchmarks.

• Production Readiness

Implement automated testing, monitoring, logging, containerized deployments, and operational documentation.

Initial Deliverables

• Review the existing codebase and recommend a production-ready architecture.
• Implement authenticated API integration, session handling, and conversation state management.
• Deliver informational workflows such as account balance, transaction history, and real-time status queries.
• Implement secure transaction preparation, validation, and user confirmation flows.
• Improve multilingual intent accuracy and establish measurable evaluation benchmarks.
• Deploy the platform to staging with automated tests and monitoring.
• Support user acceptance testing and production deployment.

What Success Looks Like

• Users can interact naturally in English, Hindi, and Hinglish.
• The assistant accurately understands requests and extracts relevant information.
• Ambiguous requests trigger meaningful clarification.
• Responses and transaction results are verified against authoritative backend systems.
• Sensitive operations require authentication, authorization, and explicit user confirmation.
• API failures are handled gracefully without duplicate transactions or misleading responses.
• The platform is scalable, maintainable, observable, and ready for future integrations.

How to Apply

Please share

• Your résumé or professional profile.
• Examples of backend or full-stack applications you have developed.
• At least one LLM integration project, including your role and technical contributions.
• A brief explanation of how you would securely connect an AI assistant to APIs that perform financial or account-related operations.

We're looking for developers who can build and ship real AI-powered applications, not just chatbot prototypes.