Full stack engineer building AI-native product features end to end: frontend, backend, and LLM integrations. Designs intelligent agent workflows with RAG, memory, tool use, and streaming responses, making AI systems reliable, observable, and low-latency in production using Next.js, Python, Node.js, PyTorch, and Kubernetes.
Responsibilities:
Design, develop, and deliver end-to-end product features across frontend, backend, and AI integrations.
Build AI-native product features that extend beyond conversational interfaces into persistent, goal-driven workflows.
Design and implement intelligent agent workflows capable of planning, tool utilisation, failure handling, and recovery across multiple steps.
Integrate Large Language Models (LLMs), memory capabilities, Retrieval-Augmented Generation (RAG), and external tools into reliable production systems.
Develop real-time AI interactions with streaming responses, partial results, and low-latency performance.
Improve AI response times while maintaining output quality and reliability.
Build robust fallback, monitoring, observability, and recovery mechanisms for AI models and external tool failures.
Continuously improve the reliability and success rate of AI-driven workflows through monitoring, evaluation, and iterative enhancements.
Develop scalable architecture and reusable patterns for integrating LLMs, memory, and external services into production systems.
Collaborate closely with Machine Learning, Backend, and Product teams to deliver high-quality product features.
Continuously enhance product performance based on production usage, user feedback, and real-world system behaviour.
Contribute to delivering a proactive, dependable, and consistent AI user experience.
Requirements:
Proven experience in full stack software engineering, covering both frontend and backend development.
Strong understanding of software architecture, system design, and API development.
Experience working with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, or AI-powered applications.
Ability to make sound engineering decisions in ambiguous and rapidly evolving environments.
Strong ownership mindset with the ability to take features from concept through to production deployment.
Comfortable working in a fast-paced environment with evolving business and technical requirements.
Technical Environment
Next.js
Python
Node.js
PyTorch
OpenAI, Anthropic and open-source Large Language Models (LLMs)
SQL & NoSQL databases
Kubernetes
Docker
To apply, please visit and search for Job Reference:
W34W69RW
To learn more about this opportunity, please contact Yingying at (HIDDEN TEXT)
We regret that only shortlisted candidates will be notified.
GMP Technologies (S) Pte Ltd | EA Licence: 11C3793 | EA Personnel: Lai Yingying | Registration No: R1110239