Software Engineer - Frontend, Backend, or Full Stack AI

About the Role Our client is a well-funded AI technology company building next-generation intelligent products powered by large language models (LLMs) and autonomous agent frameworks Frontend Engineer (AI Products) Key Responsibilities Build and maintain production-grade web interfaces, including complex management and visualisation platforms, internal operations systems, and interactive end-user applicationsEstablish and own frontend infrastructure — including reusable component libraries, design systems, coding standards, package management, and engineering scaffolding to support rapid 0→1 deliveryDrive performance and accessibility improvements across first-screen rendering, interaction responsiveness, network efficiency, bundle optimisation, internationalisation (i18n), and cross-platform compatibilityCraft data-intensive user experiences involving complex tables, filtering systems, workflow orchestration, monitoring dashboards with real-time state synchronisation, permission views, and audit trailsOwn end-to-end delivery from requirements clarification and prototype implementation through API contract definition, canary releases, rollback planning, and post-launch quality metricsIntegrate AI-assisted development tools into daily engineering workflows, evaluate their impact on team productivity, and establish and share team-level best practicesCollaborate closely with Product, Algorithm, and Engineering teams to co-define interaction patterns and user experience standards for next-generation AI featuresParticipate 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 applicationsStrong command of modern styling and component tooling (e.g. Tailwind CSS, component libraries), with experience in component abstraction, theming systems, and accessibility (a11y) implementationSolid 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 routingDeep understanding of browser rendering fundamentals — including the rendering pipeline, event loop, task scheduling, and garbage collection — with the ability to diagnose and resolve complex performance issues using tools such as Lighthouse and browser performance profilersFamiliarity 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 =============================================================== Backend Engineer Key Responsibilities Design and develop robust backend APIs, handling task orchestration, state management, and streaming responses for LLM and agent-based productsBuild and maintain scalable service infrastructure covering authentication, quota management, caching, asynchronous task processing, and service governanceImplement and optimise data pipelines for model call logging, trajectory recording, usage analytics, and cost monitoringDrive 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 microservicesApply an AI-native engineering mindset by actively leveraging AI-assisted coding tools and agentic development workflows in day-to-day engineeringCollaborate cross-functionally with product, ML, and platform teams to ship high-quality, well-tested, and well-documented backend systemsContribute 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 loggingSolid experience with microservice architecture and distributed systems designHands-on experience with relational and non-relational data stores such as MySQL, PostgreSQL, Redis, and MongoDBHigh engineering standards with a track record of delivering production-grade systems with attention to code quality, testing, and documentation =============================================================== Full-Stack Engineer 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 integrationsDevelop and manage application infrastructure layers covering prompt engineering, tool integrations, skill frameworks, and model context protocol (MCP) implementationsDesign and operate scalable backend services encompassing authentication, quota management, caching, asynchronous task processing, data pipelines, and service governanceImplement robust observability practices including monitoring, alerting, canary releases, and production troubleshooting to ensure system reliabilityChampion AI-native engineering paradigms such as vibe coding, agentic workflows, and human-in-the-loop development processes to continuously raise engineering productivityProductise complex AI use cases end-to-end and drive ongoing optimisation across performance, cost efficiency, interaction quality, and delivery speedCollaborate cross-functionally with algorithm researchers, product managers, and designers to translate AI capabilities into polished, production-ready featuresContribute 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 experienceStrong 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 VueHands-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 If you are passionate about technology and meet the above requirements, please don't hesitate to apply. Please note that only shortlisted candidates will be contacted. Appreciate your understanding. Data provided is for recruitment purposes only. Dada Consultants Pte Ltd Website: www.dadaconsultants.com EA License No.: 18S9037 Business Registration Number: 201735941W