Full Stack Software 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

The role offers a competitive monthly base salary ranging from SGD 4,800 to 7,200 complemented by annual performance-based bonuses that reward excellence and results.

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.

Requirements

• Diploma/Degree or post graduate 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.

Preferred skills and experiences

• Experience with LLM providers and APIs such as OpenAI, Anthropic, Azure OpenAI, or open-source models.
• Experience with prompt engineering, RAG, embeddings, vector databases, or AI agent frameworks.
• Understanding of security concepts for both traditional software systems and AI systems.
• Experience with observability tools, logging, tracing, metrics, and alerting.
• Prior experience in a startup, fast-paced product team, or applied AI environment.

Why you should apply

• Build real products that combine software engineering and applied AI.
• Work on agentic AI systems, LLM-powered workflows, and production-grade AI infrastructure.
• Move fast in a flat, low-bureaucracy environment.
• Work closely with product, research, and engineering teams from idea to production.
• Learn through courses, seminars, conferences, and hands-on experimentation.
• Gain access to cutting-edge AI tools, platforms, and technologies.
• Contribute to new product ideas and practical innovation.
• Play a role in strengthening Singapore’s position as a thriving innovation hub.