Full-Stack AI Systems Engineer

Knoveleng; Singapore; On-site; SGD 54,000 - 80,000; Full time

Job summary

Knoveleng is seeking an engineer to design and implement agentic AI workflows and AI-powered systems in Singapore. You will build AI Ops pipelines, integrate LLMs and APIs, and ensure reliability, scalability, and observability across production services.

Responsibilities include deploying containerized services with Docker and Kubernetes, defining API contracts, and collaborating with product, research, and engineering teams to move AI features from prototype to production.

Qualifications

• Diploma/Degree in Information System, Computer Science or Computer Engineering or equivalent.
• At least 1–6 years of experience building full stack applications, backend services, APIs, and production software systems.
• Working knowledge of Golang, or willingness to ramp up quickly.
• Experience with cloud and on-premise infrastructure.
• Experience with Docker and good-to-have experience with Kubernetes.
• Hands-on experience building or operating AI-powered systems, agentic workflows, or LLM-based applications.
• Familiarity with agent orchestration concepts such as multi-step reasoning flows, tool use, memory, multiple LLM calls, and multi-agent workflows.
• Practical understanding of AI Ops or MLOps concepts, including model or prompt versioning, evaluation pipelines, monitoring, observability, and production support.
• Solid understanding of system design principles, including scalability, reliability, caching, load balancing, and distributed systems trade-offs.
• Experience designing and consuming APIs such as REST, gRPC, or GraphQL, including authentication, versioning, and documentation.
• Experience with databases, schema design, query optimization, and data flow design.
• Strong debugging, problem-solving, communication, and ownership mindset.
• Comfortable working in a fast-moving startup environment with evolving priorities.

Responsibilities

• Design and implement agentic AI workflows, including multi-step tasks, tool-using agents, memory, and multi-agent orchestration.
• Build and maintain AI Ops pipelines for LLM-powered systems, including deployment, monitoring, evaluation, prompt and version management, cost tracking, and observability.
• Integrate LLMs, AI models, APIs, data sources, and internal tools into production systems.
• Architect scalable systems covering service boundaries, data flow, caching, queues, retries, failure handling, and performance.
• Design clean database schemas and write efficient, reliable queries.
• Define and implement well-documented API contracts for internal and external users.
• Containerize and deploy services using Docker and Kubernetes.
• Work closely with product, research, and engineering teams to bring AI features from prototype to production.
• Own the reliability, scalability, and performance of the systems you build, including monitoring, alerting, debugging, and incident response.
• Participate in code reviews, architecture discussions, technical planning, and product discovery.
• Move fast, ship thoughtfully, and continuously improve engineering quality.
• Collaborate with relevant stakeholders throughout the Software Development Life Cycle (SDLC).
• Contribute to technical documentation, runbooks and knowledge sharing to support long-term maintainability.

Skills

Golang

Docker

Kubernetes

API design

AI systems

Observability

Education

Bachelor's or Diploma in CS/IS/CE

Tools

REST APIs

gRPC

GraphQL

Job description

Knoveleng is seeking an engineer to design and implement agentic AI workflows and AI-powered systems in Singapore. You will build AI Ops pipelines, integrate LLMs and APIs, and ensure reliability, scalability, and observability across production services.

Responsibilities include deploying containerized services with Docker and Kubernetes, defining API contracts, and collaborating with product, research, and engineering teams to move AI features from prototype to production.