About the Client
Our 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.
Responsibilities
- Build full-stack AI product capabilities — LLM / multimodal / Agent UI, backend APIs, task workflows, state management, and service integrations
- Build application infrastructure — Prompt / Skills / MCP / Tools integration, driving models from experimental prototypes to stable, deliverable product capabilities
- Build scalable backend services — auth, quotas, caching, async tasks, data processing, service governance, canary releases, monitoring, and alerting
- Drive AI-native engineering paradigms — vibe coding tools, Harness Engineering, Agentic Workflows, and Human-in-the-Loop practices
- Productize complex AI scenarios — translate research capabilities into stable, user-facing products; continuously optimize performance, cost, interaction quality, and delivery efficiency
Requirements
- Proficient in Python / Golang / TypeScript (one or more), with full-stack collaborative development experience across complete business systems
- Backend & frontend: API design, permission control, task scheduling, async processing, caching, logging, service governance, microservice architecture; familiar with React / Next.js / Vue
- AI application engineering: LLM app development, Prompt engineering, Tool Use, Skills, MCP, Workflow / Agent patterns; strong interest in adopting emerging AI technologies
- AI-native development: proficient with vibe coding tools, with AI-assisted development deeply integrated into daily engineering practice
- Data storage & modeling: MySQL / PostgreSQL + Redis / MongoDB, with basic modeling and performance optimization skills; vector retrieval experience is a plus
- Delivery & observability: Git, Docker, CI/CD; basic Kubernetes; Prometheus / Grafana monitoring
Nice to Have
- Experience delivering AI products, Agents, Copilots, workflow systems, or multimodal applications
- Familiarity with the MCP ecosystem, or hands-on experience with Skills / Tools / Plugins / Function Calling
- Practical understanding of Harness Engineering, Human-in-the-Loop practices, or Agentic Coding Workflows
- Experience building complex platform systems, admin portals, or AI applications
- Deep expertise in frontend engineering, infrastructure, or data pipelines beyond your primary language
- Open-source contributions, technical blog posts, papers, or talks demonstrating continuous learning
- Strong sensitivity to AI product experience — caring about user value and business outcomes, not just technical implementation
AIM Global Talent Pte. Ltd. | EA Licence No. 25C3207