Senior Full-Stack AI Engineer – Production-Ready Systems

Knoveleng; Singapore; On-site; SGD 67,000 - 80,000; Full time

Job summary

Knovleng is seeking an engineer to build practical AI-powered systems at scale in Singapore. You will implement agentic AI workflows, design robust APIs, and containerize services for production use.

The role blends software engineering with applied AI, demanding high performance, observability, and reliable deployments. You will collaborate across product, research and engineering teams to move ideas from prototype to live systems, owning reliability and performance while shipping iteratively

Qualifications

• 3–6+ years building full stack apps, APIs, and production systems.
• Experience with Golang or ability to ramp quickly.
• Familiar with Docker and at least knowledge of Kubernetes.
• Experience with cloud and on-prem infrastructure.

Responsibilities

• Design and implement AI workflows with multi-step tasks and tool-using agents.
• Build AI Ops pipelines for LLM-powered systems including deployment and observability.
• Integrate AI models, APIs, data sources and internal tools into production systems.
• Architect scalable services with data flow, caching, queues, retries and fault tolerance.
• Design clean DB schemas and write efficient queries.
• Define documented API contracts for internal/external users.
• Containerize and deploy services using Docker and Kubernetes.
• Collaborate with product, research and engineering to productionize AI features.

Skills

Golang

API design

Docker

Kubernetes

Cloud computing

Observability

AI/ML integration

Distributed systems

Code reviews

Problem solving

Education

Diploma/ Degree in Information Systems or CS

Tools

Terraform

Ansible

Job description

Knovleng is seeking an engineer to build practical AI-powered systems at scale in Singapore. You will implement agentic AI workflows, design robust APIs, and containerize services for production use.

The role blends software engineering with applied AI, demanding high performance, observability, and reliable deployments. You will collaborate across product, research and engineering teams to move ideas from prototype to live systems, owning reliability and performance while shipping iteratively