Node.js Backend Engineer

Backend Engineer Node.js, APIs & Production Services Mumbai (On-site) | Full-time | 3-5 years

Unico Connect is an AI-first technology partner that builds custom mobile, web, and AI products for clients across multiple geographies. We are hiring a Backend Engineer for a dedicated client engagement building an AI-powered application builder platform. The backend is the operational core of the product: it manages user projects and sessions, coordinates long-running AI agent workloads, maintains project state, and serves as the integration layer between the frontend, the AI system, and the underlying infrastructure. The mandatory requirement is hands-on production experience shipping Node.js services, with end-to-end ownership of API design, data modelling, and at least one production system involving background job processing or event-driven patterns.

is hands-on and collaborative. You will work closely with the Senior AI Engineer and MLOps Engineer on agent task coordination, and with the frontend team on API contracts and real-time communication. A typical week includes a schema migration for a new product feature, integrating a new AI agent capability into the backend API, debugging a queue backlog under load, and a code review session with peers.

API and service development: Design and build REST APIs in Node.js with TypeScript. Cover authentication, session management, input validation, structured error handling, streaming responses (Server-Sent Events, WebSockets), and rate limiting. Maintain clean API contracts that the frontend and AI system can rely on. Database design and management: Own PostgreSQL schema design for product domains including user accounts, projects, file trees, session state, and generated artefacts. Write efficient queries, manage migrations, and optimise for read patterns that serve a real-time editor experience. Think carefully about data isolation between tenants. Caching strategy: Implement and maintain caching with Redis for session data, project state, and frequently read configuration. Design cache invalidation logic that keeps the editor experience consistent without stale reads. Queue and background job management: Implement and operate background job infrastructure using BullMQ or equivalent. AI agent runs are long-running and stateful; the backend must enqueue, track, and surface the progress and results of these workloads reliably. Handle retries, failure states, priority queues, and concurrency limits. AI system integration: Build the integration layer between the backend and the AI agent system. Manage job dispatch, result handling, streaming output to the frontend, and error propagation. Treat AI agent calls as unreliable external dependencies and build accordingly. Multi-tenancy and access control: Implement tenant data isolation, RBAC, and resource ownership enforcement across all API surfaces. Ensure one user's data and agent workloads cannot affect another's. Observability and reliability: Instrument services with structured logging, metrics, and tracing. Write defensive code with sensible timeouts, fallback behaviour, and circuit breaking on external dependencies. Participate in incident response and postmortems. Testing and code quality: Write unit and integration tests for the services you ship. Review the work of peers and contribute to shared engineering conventions across the backend.