AI Application Developer
Develops and integrates AI-powered features like chatbots and RAG workflows using FastAPI, React, and LangChain, while supporting the full AI pipeline from data ingestion to deployment.
- Compensation
- SGD 5.2K–SGD 6K / mo
- Location
- Singapore
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Software engineering
- Posted
Skills
Must have
- Strong programming skills in Python (FastAPI, Flask, or Django) and/or JavaScript/TypeScript (React, Node.js).
- Familiarity with REST APIs, JSON, YAML configurations.
- Experience building workflows or backend services.
Full description
About the Role
The AI Application Developer builds and integrates AI-powered capabilities into enterprise applications and platforms. This role designs and delivers production ready features such as conversational assistants, AI agent workflows, and retrieval augmented generation (RAG) components, working closely with the Solution Architect, Project and Product Manager, and AI engineers.
The role also supports the end to end AI pipeline, including data ingestion and parsing, embedding and indexing, retrieval, prompt and orchestration workflows, evaluation, and continuous improvement through feedback. The initial focus is on the AI in a Box platform, but the role will also support other AI projects across Product Engineering. As priorities evolve, the developer will be assigned to other AI initiatives, including new AI products, automation workflows, and enterprise integrations, while ensuring solutions are secure, maintainable, and ready for deployment.
Key Responsibilities1. Application Development
- Design, develop, and maintain application features in backend (FastAPI, n8n) and/or frontend (React + Tailwind).
- Implement APIs, workflows, and integrations with enterprise systems (SharePoint, OneDrive, Jira, HRMS).
- Build reusable components for AI agents (Meeting Minutes, Document Comparison, Self-Service Assistants)
2. AI Integration
- Work with AI/LLM engineers to integrate LangChain pipelines, RAG workflows, and prompt templates.
- Implement context injection and feedback loops for AI agents.
- Handle text parsing (Apache Tika, PaddleOCR) and data preparation for embeddings.
3. Quality & Testing
- Write clean, testable, and maintainable code.
- Contribute to unit/integration tests, debugging, and bug fixes.
- Work with QA engineers to ensure smooth releases.
4. Collaboration
- Participate in sprint planning, standups, and code reviews.
- Work under guidance of the Solution Architect, following best practices for CI/CD and deployment.
- Collaborate with frontend/backend peers to ensure seamless integration.
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Required Skills & Experience1. Core Development
- Strong programming skills in Python (FastAPI, Flask, or Django) and/or JavaScript/TypeScript (React, Node.js).
- Familiarity with REST APIs, JSON, YAML configurations.
- Experience building workflows or backend services.
2. AI & Data Handling
- Exposure to AI/ML libraries (LangChain, HuggingFace, OpenAI APIs) is a plus.
- Ability to integrate AI models into applications (e.g., LLM-based chat, RAG search).