Full Stack Engineer, AI

TECHKNOWLEDGEY PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

TECHKNOWLEDGEY PTE. LTD. is seeking a Full Stack Engineer - AI to translate core intelligence into production-grade workflows, spanning frontend interfaces to AI-inference pipelines.

You will design autonomous agent operations, handle failures, and deliver dependable value across interactions, collaborating with ML, backend and product teams to ship high-impact features.

Qualifications

• Demonstrated experience in full-stack engineering across modern frontend and backend tech.
• Strong grasp of scalable system design and robust API architecture.
• Practical AI/LLM experience with production-grade workflows.
• Ability to navigate ambiguity with sound technical judgment.
• Proven ownership from concept to production deployment.

Responsibilities

• Architect and build end-to-end features across the stack linking frontend clients with backend services and AI inference.
• Design sophisticated agent workflows including multi-step planning, tool use, and recovery across sessions.
• Integrate LLMs, retrieval-augmented generation, and external tools into cohesive systems.
• Develop real-time interfaces supporting streaming responses with low latency.
• Improve reliability, observability, and fallback mechanisms for non-deterministic components.
• Collaborate with ML, backend and product teams to ship high-impact features.

Skills

Full Stack Engineering

System Architecture

AI & LLM Application

Pragmatic Decision Making

Ownership & Execution

Tools

Next.js

Python

Node.js

PyTorch

OpenAI API

Anthropic API

Open-Source LLLMs

SQL

NoSQL

Kubernetes

Docker

Job description

We are seeking a Full Stack Engineer - AI to build the product layer that translates core intelligence capabilities into usable, production-grade workflows. This role encompasses designing how autonomous agents operate, handle failures, execute recovery sequences, and deliver consistent, dependable value to users across every interaction.

You will engineer end-to-end product features spanning frontend interfaces, backend orchestration services, and deep AI integrations, ensuring seamless operation under real-world conditions.

Core Responsibilities

• End-to-End Product Engineering: Architect and build robust features across the entire stack, connecting modern frontend clients with backend services and AI inference pipelines.
• Agent Workflow Design: Design sophisticated agent workflows capable of managing multi-step planning, tool utilization, failure detection, and automated recovery across sessions.
• LLM & Tool Integration: Integrate large language models, persistent memory layers, and external software tools into cohesive systems that behave reliably in production.
• Real-Time AI Interaction: Build responsive, real-time user interfaces supporting streaming responses, partial results, and strict latency constraints.
• Reliability & Observability: Continuously improve system reliability, monitoring, observability, and fallback mechanisms for non-deterministic model components.
• Cross-Functional Collaboration: Partner closely with machine learning, backend, and product teams to ship high-impact features seamlessly.

Ideal Experience & Background

• Full Stack Proficiency: Strong, demonstrated experience in full-stack engineering across modern frontend and backend frameworks.
• System Architecture: Solid understanding of scalable system design, distributed patterns, and robust API architecture.
• AI & LLM Application Experience: Practical experience working with large language models, retrieval-augmented generation (RAG) systems, or AI-powered product applications.
• Pragmatic Decision-Making: Demonstrated ability to navigate ambiguity, exercise strong technical judgment, and make pragmatic engineering tradeoffs.
• Ownership & Execution: Strong sense of ownership with a proven track record of taking complex features from initial concept through to production deployment.

Technical Stack

• Frontend: Next.js
• Languages: Python, Node.js
• Machine Learning & Frameworks: PyTorch, OpenAI API, Anthropic API, Open-Source LLMs
• Data Stores: SQL and NoSQL database systems
• Infrastructure & Orchestration: Kubernetes, Docker