AI Application Engineer

RAPSYS TECHNOLOGIES PTE LTD; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

RAPSYS TECHNOLOGIES PTE LTD in Singapore is seeking an experienced AI Application Engineer to design, build and deploy AI-powered enterprise applications, with a focus on performance, security and user experience. You will refactor prototypes into production-grade software, implement end-to-end AI services, and work with Azure AI services and enterprise integrations.

This role requires strong full-stack skills and a solid grounding in security and observability, within an agile team.

Qualifications

• 7+ years of hands-on software engineering experience.
• Experience building, deploying and supporting enterprise or cloud-native applications.
• Strong full-stack engineering capability across modern frontend, backend and API development frameworks such as React, TypeScript, Node.js, Python, .NET, Java or equivalent technologies.
• Hands-on experience designing and integrating REST APIs, backend services, databases, authentication mechanisms and enterprise integrations.
• Practical experience building AI-enabled applications using LLMs, RAG patterns, embeddings, vector search, agents, automation or orchestration frameworks.
• Working knowledge of Azure AI services such as Azure OpenAI, Azure AI Foundry, Azure AI Search, Azure Machine Learning and related Azure services.
• Experience applying secure software development practices including input validation, secrets management and least-privilege access.
• Familiarity with OAuth 2.0, OpenID Connect, SAML, JWT, RBAC and enterprise identity integration.
• Hands-on experience with CI/CD pipelines using Azure DevOps, GitHub Actions or equivalent.
• Knowledge of containerisation, cloud deployment patterns and production support.
• Ability to assess prototype quality and plan for production readiness.
• Understanding of AI risks, including hallucination, data leakage and prompt injection.
• Strong communication and stakeholder management skills.
• Comfortable in an agile, product-oriented environment.

Responsibilities

• Refactor prototypes into production-grade solutions with clean architecture and automated deployment pipelines.
• Design, build and harden AI-enabled applications including chatbots, RAG solutions and workflow tools.
• Collaborate with product owners to clarify use-cases, user journeys and production readiness.
• Implement full-stack capabilities across frontend, backend, APIs, data integration, authentication and monitoring.
• Integrate with approved AI services such as Azure AI and enterprise APIs.
• Apply secure and responsible AI patterns including prompt management and content safety controls.
• Develop reusable patterns and engineering playbooks for AI delivery.
• Support production-readiness assessments covering security, data classification and observability.
• Build automated test suites for AI applications and guardrail validation.
• Implement observability for AI apps including logs, latency and metrics.
• Collaborate with platform engineers to deploy using CI/CD, containerisation and API management.
• Document solution designs and procedures for maintainability.

Skills

Full-stack development

React

TypeScript

Node.js

Python

.NET

Java

REST APIs

Azure AI services

Security best practices

CI/CD

Containerisation

Observability

Job description

We are seeking a skilled and innovative AI Application Engineer to join our dynamic team in Singapore. The ideal candidate will possess extensive experience in developing and implementing AI applications, with a strong focus on optimizing performance and enhancing user experiences.

Key Responsibilities

• 1. Refactor prototypes and vibe-coded applications into production-grade solutions with clean architecture, maintainable code, secure authentication, robust APIs and automated deployment pipelines.
• 2. Design, build and harden AI-enabled applications, including chatbots, RAG solutions, workflow assistants, agents, automation tools and AI-assisted business applications.
• 3. Work with product owners and business stakeholders to clarify use-case outcomes, user journeys, operational ownership, adoption metrics and production-readiness requirements.
• 4. Implement full-stack application capabilities across frontend, backend, APIs, data integration, authentication, authorization, logging and monitoring.
• 5. Integrate applications with approved AI services such as Azure OpenAI, Azure AI Foundry, Azure AI Search, Azure Machine Learning, Microsoft Graph, enterprise APIs and internal data sources.
• 6. Apply secure and responsible AI application patterns, including prompt management, retrieval grounding, input/output controls, human-in-the-loop design, auditability and content safety controls.
• 7. Develop reusable implementation patterns, starter templates and engineering playbooks for AI application delivery across common use cases.
• 8. Support production-readiness assessments covering security, privacy, data classification, model behaviour, observability, cost, support model and operational handover.
• 9. Build automated test suites for AI applications, including functional tests, regression tests, prompt evaluation, response quality checks and guardrail validation.
• 10. Implement observability for AI applications, including application logs, model usage, latency, token consumption, errors, user feedback, cost and key business metrics.
• 11. Collaborate with platform engineers to deploy AI applications using approved cloud patterns, CI/CD pipelines, containerisation, API management, secrets management and monitoring baselines.
• 12. Document solution designs, operating procedures, reusable patterns, known limitations and support guides to ensure applications are maintainable after go-live.

Required Skills and Experience

• 1. 7+ years of hands-on software engineering experience, including experience building, deploying and supporting enterprise or cloud-native applications.
• 2. Strong full-stack engineering capability using modern frontend, backend and API development frameworks such as React, TypeScript, Node.js, Python, .NET, Java or equivalent technologies.
• 3. Hands-on experience designing and integrating REST APIs, backend services, databases, authentication mechanisms and enterprise application integrations.
• 4. Practical experience building AI-enabled applications using large language models, RAG patterns, prompt engineering, embeddings, vector search, agents, workflow automation or AI orchestration frameworks.
• 5. Working knowledge of Azure AI services such as Azure OpenAI, Azure AI Foundry, Azure AI Search, Azure Machine Learning, Azure App Service, Azure Container Apps, API Management, Key Vault, Azure Monitor and Log Analytics.
• 6. Experience applying secure software development practices, including input validation, secrets management, least-privilege access, dependency scanning, logging, error handling and secure configuration.
• 7. Experience with modern authentication and authorization standards, including OAuth 2.0, OpenID Connect, SAML, JWT, RBAC and enterprise identity integration using Microsoft Entra ID.
• 8. Hands-on experience with CI/CD pipelines using Azure DevOps, GitHub, GitHub Actions, ShipHATS or equivalent platforms.
• 9. Familiarity with containerisation, cloud deployment patterns, environment promotion, deployment rollback and production support practices.
• 10. Ability to assess prototype quality and determine what must be rebuilt, hardened, monitored or redesigned before production release.
• 11. Good understanding of AI risks, including hallucination, data leakage, prompt injection, unsafe tool use, policy bypass, privacy risks and poor explainability.
• 12. Strong documentation, communication and stakeholder management skills, with the ability to explain technical design choices and production trade-offs clearly.
• 13. Comfortable working in an agile, product-oriented environment where solutions are delivered iteratively and improved through user feedback, platform patterns and governance review.