Full Stack Developers (AMK)

MAESTRO HUMAN RESOURCE PTE. LTD.; Singapore; On-site; SGD 48,000 - 72,000; Full time

Job summary

MAESTRO HUMAN RESOURCE PTE. LTD. is seeking a Full Stack Developer to design, develop, and maintain web-based applications in Singapore. The role includes responsibilities in system integration, testing, and deployment support, ensuring alignment with enterprise architecture standards.

The ideal candidate will have proficiency in modern front-end and back-end technologies, a strong foundation in database management, and experience with secure coding practices. This position offers opportunities for professional development and collaboration within a structured project environment.

This role supports a 5-day workweek in the AMK Area.

Qualifications

• 3 to 5 years of hands-on full stack development experience.
• Ability to write and optimize SQL queries.
• Relevant certifications in software development or cloud technologies.

Responsibilities

• Design, develop, test, and maintain web-based applications.
• Build user-friendly interfaces based on UX requirements.
• Provide technical support for production applications.

Skills

Proficiency in front-end frameworks (React.js, Angular, Vue.js)

Strong knowledge of HTML5, CSS3, JavaScript/TypeScript

Experience in back-end technologies (Java/Spring Boot, .NET/C#, Node.js, Python)

Database experience (PostgreSQL, MS SQL Server, Oracle, MySQL)

Experience with Git and issue tracking tools (Jira, Azure DevOps)

Education

Diploma or Degree in Computer Science or related discipline

Tools

Docker

Kubernetes

Job description

We areseeking a Senior Full‑Stack Developer with deep expertise in both deepbackend (Priority) and well-understanding frontend technologies to buildand maintain the scalable systems that power our AI and LLM‑based products. While the role expands to full‑stack responsibilities, the core focus remains on designingrobust backend services, integrating machine‑learning models, and managing theinfrastructure that supports large language models.

Key Responsibilities

• Design& implement backend services and APIs using Golang and Python (including micro‑services architecture)
• Collaborate with ML engineers to deploy, monitor, and integrate machine‑learning models into production pipelines
• Develop and maintain infrastructure for LLMs and AI agents, ensuring high performance, scalability, and reliability
• Manage and optimize databases (MySQL, MongoDB) and work with vector databases or RAG systems where needed
• Utilize AI‑assisted coding tools such as Codex and Claude Code to accelerate development
• Build modern, responsive UI components using React and MUI5, delivering seamless user experiences.
• Implement server‑side logic with Java, Spring, and Spring Boot, enabling robust, enterprise‑grade services.
• Deploy and orchestrate applications on Kubernetes clusters, leveraging AWS and Azure infrastructure services.

Required Qualifications

• Bachelor’s degree (or higher) in Computer Science, Data Science, or a related field.
• 5+years of professional experience in backend development (Golang/Python) and full‑stack development (React, Java/Spring).
• Strong understanding of AI Agentic workflows and experience integrating ML models into production
• Proven experience with MySQL, MongoDB, and optionally vector databases or RAG systems
• Hands‑on experience with micro‑services, cloud platforms (AWS, GCP,Azure) and container orchestration (Kubernetes)
• Familiarity with LLM and AI‑agent frameworks, and the ability to build supporting infrastructure

Bonus Skills

• Experience with MUI5 for building modern UI components.
• Proficiency in React (hooks, context, performance optimization).
• Strong Java development background, especially with Spring and Spring Boot.
• Knowledgeof Kubernetes advanced concepts (Helm, operators, CI/CD pipelines).
• Hands‑on experience managing AWS services (ECS/EKS, Lambda, S3,RDS) and Azure services (AKS, Functions, Cosmos DB).
• Exposure to ML Ops tools such as ML flow, Kubeflow, SageMaker.
• Experience with vector databases, retrieval‑augmented generation (RAG) systems, or embeddings.