Software Engineer (Multiple HC - Frontend/Backend/Fullstack) - AI/ IT/ Fintech/Internet

Dada Consultants; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Our client is an AI technology company building next-generation intelligent products powered by LLMs and autonomous frameworks. You will design and ship production-ready web interfaces, design systems, and scalable frontend infrastructure.

Collaborate with product and engineering teams on interaction standards, instrumentation, and best practices while driving performance and accessibility improvements across complex client dashboards and admin tools.

Qualifications

• Proficiency in TypeScript / React / Next.js, with hands-on experience shipping production web applications.
• Strong command of modern styling and component tooling (Tailwind CSS) with theming and accessibility.
• Solid grasp of state and data management patterns (Zustand, Redux, TanStack Query) and common UI patterns such as forms and tables.
• Familiarity with frontend tooling (Vite, Turborepo, Monorepo) and testing frameworks (Jest/Vitest) plus end-to-end tools (Playwright or Cypress).

Responsibilities

• Design and build robust frontend interfaces for complex management and visualisation platforms.
• Own frontend infrastructure including reusable components, design systems, and engineering scaffolding.
• Improve performance, accessibility, i18n, and cross‑platform compatibility across first-screen rendering.
• Create data‑driven UIs with complex tables, filters, dashboards, and audit trails.
• Lead end‑to‑end delivery from requirements to post‑launch metrics and canary releases.
• Integrate AI-assisted development tools and promote best practices across the team.
• Collaborate with product, algorithm, and engineering teams on interaction patterns and standards.
• Participate in code reviews and uphold linting and formatting standards.

Skills

TypeScript

React

Next.js

UI architecture

Accessibility

State management

Testing frameworks

Performance optimization

Zustand

Redux

TanStack Query

Tools

Tailwind CSS

Jest

Vitest

Playwright

Cypress

Vite

Turborepo

Monorepos

Job description

Our client is a well-funded AI technology company building next-generation intelligent products powered by large language models (LLMs) and autonomous agent frameworks

Key Responsibilities

• Build and maintain production-grade web interfaces, including complex management and visualisation platforms, internal operations systems, and interactive end-user applications


• Establish and own frontend infrastructure - including reusable component libraries, design systems, coding standards, package management, and engineering scaffolding to support rapid 0→1 delivery


• Drive performance and accessibility improvements across first-screen rendering, interaction responsiveness, network efficiency, bundle optimisation, internationalisation (i18n), and cross-platform compatibility


• Craft data-intensive user experiences involving complex tables, filtering systems, workflow orchestration, monitoring dashboards with real-time state synchronisation, permission views, and audit trails


• Own end-to-end delivery from requirements clarification and prototype implementation through API contract definition, canary releases, rollback planning, and post-launch quality metrics


• Integrate AI-assisted development tools into daily engineering workflows, evaluate their impact on team productivity, and establish and share team-level best practices


• Collaborate closely with Product, Algorithm, and Engineering teams to co-define interaction patterns and user experience standards for next-generation AI features


• Participate in code reviews, enforce lint and formatting standards, and contribute to a culture of engineering rigour and continuous improvement

Requirements

• Proficiency in TypeScript / React / Next.js (including App Router, SSR/SSG/ISR, and Server Actions), with hands-on experience shipping production web applications


• Strong command of modern styling and component tooling (e.g. Tailwind CSS, component libraries), with experience in component abstraction, theming systems, and accessibility (a11y) implementation


• Solid grasp of state and data management patterns (e.g. Zustand, Redux, TanStack Query) and mature handling of common UI patterns such as forms, tables, and client-side routing


• Familiarity with modern frontend engineering tooling (e.g. Vite, Turborepo, Monorepo structures) and experience with testing frameworks such as Jest/Vitest and end-to-end testing tools such as Playwright or Cypress

Key Responsibilities

• Design and develop robust backend APIs, handling task orchestration, state management, and streaming responses for LLM and agent-based products


• Build and maintain scalable service infrastructure covering authentication, quota management, caching, asynchronous task processing, and service governance


• Implement and optimise data pipelines for model call logging, trajectory recording, usage analytics, and cost monitoring


• Drive model integration work including prompt engineering, tool-use frameworks, and agentic workflow design using modern AI tooling protocols (e.g. MCP)


• Own service reliability through monitoring, alerting, and observability practices across distributed microservices


• Apply an AI-native engineering mindset by actively leveraging AI-assisted coding tools and agentic development workflows in day-to-day engineering


• Collaborate cross-functionally with product, ML, and platform teams to ship high-quality, well-tested, and well-documented backend systems


• Contribute to engineering standards across code quality, testing practices, and internal technical documentation

Requirements

• Proficiency in Golang and Python, with strong backend engineering fundamentals including API design, authentication, task scheduling, caching, and logging


• Solid experience with microservice architecture and distributed systems design


• Hands-on experience with relational and non-relational data stores such as MySQL, PostgreSQL, Redis, and MongoDB


• High engineering standards with a track record of delivering production-grade systems with attention to code quality, testing, and documentation

Key Responsibilities

• Build and maintain full-stack AI product capabilities, including LLM-powered features, multimodal interfaces, agent UIs, backend APIs, task workflows, state management, and third-party service integrations


• Develop and manage application infrastructure layers covering prompt engineering, tool integrations, skill frameworks, and model context protocol (MCP) implementations


• Design and operate scalable backend services encompassing authentication, quota management, caching, asynchronous task processing, data pipelines, and service governance


• Implement robust observability practices including monitoring, alerting, canary releases, and production troubleshooting to ensure system reliability


• Champion AI-native engineering paradigms such as vibe coding, agentic workflows, and human-in-the-loop development processes to continuously raise engineering productivity


• Productise complex AI use cases end-to-end and drive ongoing optimisation across performance, cost efficiency, interaction quality, and delivery speed


• Collaborate cross-functionally with algorithm researchers, product managers, and designers to translate AI capabilities into polished, production-ready features


• Contribute to engineering best practices, internal tooling, and the continuous improvement of the team's development lifecycle

Requirements

• Proficiency in one or more of the following languages: Python, Golang, or TypeScript, with solid full-stack collaborative development experience


• Strong backend and frontend engineering fundamentals including API design, permission control, task scheduling, asynchronous processing, caching, logging, microservice architecture, and familiarity with frameworks such as React, Next.js, or Vue


• Hands-on experience with AI application engineering, including LLM app development, prompt design, tool use, workflow orchestration, and agent patterns (e.g. MCP, Skills, Function Calling)


• Competency with common data storage technologies (MySQL, PostgreSQL, Redis, MongoDB) and DevOps tooling including Git, Docker, CI/CD pipelines, Kubernetes, Prometheus, and Grafana