Full Stack AI Engineer

About the ClientOur client is a fast-growing AI infrastructure company building foundational systems for large-scale model training and deployment. The team works at the intersection of applied AI research and production engineering — turning cutting-edge model capabilities into robust, scalable infrastructure that powers real-world AI products. Backed by a strong technical culture and rapid iteration pace, the company is expanding its engineering team to support growing infrastructure and platform demands across training, inference, and agentic systems.ResponsibilitiesBuild full-stack AI product capabilities — LLM / multimodal / Agent UI, backend APIs, task workflows, state management, and service integrationsBuild application infrastructure — Prompt / Skills / MCP / Tools integration, driving models from experimental prototypes to stable, deliverable product capabilitiesBuild scalable backend services — auth, quotas, caching, async tasks, data processing, service governance, canary releases, monitoring, and alertingDrive AI-native engineering paradigms — vibe coding tools, Harness Engineering, Agentic Workflows, and Human-in-the-Loop practicesProductize complex AI scenarios — translate research capabilities into stable, user-facing products; continuously optimize performance, cost, interaction quality, and delivery efficiencyRequirementsProficient in Python / Golang / TypeScript (one or more), with full-stack collaborative development experience across complete business systemsBackend & frontend: API design, permission control, task scheduling, async processing, caching, logging, service governance, microservice architecture; familiar with React / Next.js / VueAI application engineering: LLM app development, Prompt engineering, Tool Use, Skills, MCP, Workflow / Agent patterns; strong interest in adopting emerging AI technologiesAI-native development: proficient with vibe coding tools, with AI-assisted development deeply integrated into daily engineering practiceData storage & modeling: MySQL / PostgreSQL + Redis / MongoDB, with basic modeling and performance optimization skills; vector retrieval experience is a plusDelivery & observability: Git, Docker, CI/CD; basic Kubernetes; Prometheus / Grafana monitoringNice to HaveExperience delivering AI products, Agents, Copilots, workflow systems, or multimodal applicationsFamiliarity with the MCP ecosystem, or hands-on experience with Skills / Tools / Plugins / Function CallingPractical understanding of Harness Engineering, Human-in-the-Loop practices, or Agentic Coding WorkflowsExperience building complex platform systems, admin portals, or AI applicationsDeep expertise in frontend engineering, infrastructure, or data pipelines beyond your primary languageOpen-source contributions, technical blog posts, papers, or talks demonstrating continuous learningStrong sensitivity to AI product experience — caring about user value and business outcomes, not just technical implementationAIM Global Talent Pte. Ltd. | EA Licence No. 25C3207