Full Stack Developer (AI)

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

Job summary

Doist is seeking a Full Stack Engineer – AI Systems in Singapore to build the product layer that turns AI capabilities into usable, production-grade workflows. You will design how agents operate, fail, recover, and deliver consistent value to users.

Focus on end-to-end features across frontend, backend, and AI integrations; design robust agent workflows; integrate LLMs and external tools; ensure real-time AI interactions with low latency and high reliability.

Qualifications

• Strong experience in full stack engineering (frontend + backend).
• Solid understanding of system design and API architecture.
• Experience working with LLMs, RAG systems, or AI-powered applications.
• Ability to handle ambiguity and make pragmatic engineering decisions.
• Strong ownership - able to take features from idea to production.
• Comfort working in fast-moving environments with evolving requirements.

Responsibilities

• Build end-to-end product features across frontend, backend, and AI integrations.
• Design agent workflows that handle planning, tool use, failure, and recovery.
• Integrate LLMs, memory, and external tools into reliable systems.
• Create real-time AI interactions with streaming and low latency.
• Improve reliability, observability, and fallback mechanisms.
• Collaborate with ML, backend, and product teams to ship features.

Skills

Full stack engineering

System design & API architecture

LLMs / AI-powered apps

Ambiguity tolerance & pragmatic decyz

Ownership & end-to-end delivery

Fast-moving environment adaptability

Tools

Next.js

Python

Node.js

PyTorch

LLMs / OpenAI / Anthropic

SQL & NoSQL

Kubernetes

Docker

Job description

Full Stack Engineer – AIRoleWe are looking for a Full Stack Engineer - AI Systems to build the product layer that turns these capabilities into usable, production-grade workflows. This includes designing how agents operate, fail, recover, and deliver consistent value to users.

FocusBuild end-to-end product features across frontend, backend, and AI integrationsDesign agent workflows that handle planning, tool use, failure, and recovery across multiple steps. Integrate LLMs, memory, and external tools into systems that behave reliably under real-world conditionsDesign real-time AI interactions with streaming, partial results, and tight latency constraintsImprove system reliability, observability, and fallback mechanismsCollaborate closely with ML, backend, and product teams to ship features end-to-endContinuously iterate based on real usage and failure modes

Ideal Experiences

• Strong experience in full stack engineering (frontend + backend)
• Solid understanding of system design and API architecture
• Experience working with LLMs, RAG systems, or AI-powered applications
• Ability to handle ambiguity and make pragmatic engineering decisions
• Strong ownership - able to take features from idea to production
• Comfort working in fast-moving environments with evolving requirements

Outcomes

• Own and ship AI-native product features that move beyond chat into persistent, goal-driven workflows
• Design and deploy agent workflows that reliably complete multi-step tasks across tools and sessions
• Reduce latency and improve responsiveness of AI interactions while maintaining output quality
• Build robust fallback and recovery mechanisms for LLM and tool failures in production environments
• Improve the success rate and reliability of AI-driven workflows through iteration, evaluation, and monitoring
• Establish patterns and abstractions for integrating LLMs, memory, and external tools into scalable product systems
• Contribute to a product experience where AI feels proactive, consistent, and dependable over time

Tech Stack

• Next.js
• Python
• NodeJs
• Pytorch
• OpenAI / Anthropic / open-source LLMs
• SQL & noSQL
• Kubernetes
• Docker