AI Application Developer

Genesis Networks Pte Ltd; Singapore; On-site; SGD 90,000 - 140,000; Full time

Job summary

Genesis Networks Pte Ltd in Singapore is seeking an AI Application Developer to design and deliver production-ready AI features across enterprise apps, including conversational agents and RAG components, collaborating with the Solution Architect, Project and Product Manager, and AI engineers.

The role supports data ingestion, embedding, retrieval, and orchestration workflows, with initial focus on the AI in a Box platform and expansion to other AI initiatives while ensuring secure, maintainable

Qualifications

• Strong programming in Python and JavaScript/TypeScript for backend/frontend.
• Experience with REST APIs, JSON, and YAML configurations.
• Familiarity with AI/ML libraries and integrating AI models into applications.
• Knowledge of CI/CD workflows and container orchestration tools is a plus.

Responsibilities

• Design, develop, and maintain application features in backend (FastAPI) and frontend (React).
• Implement APIs, workflows, and integrations with enterprise systems (SharePoint, Jira, HRMS).
• Build reusable components for AI agents (Meeting Minutes, Document Comparison, Self-Service Assistants).
• Collaborate with LangChain pipelines, RAG workflows, and prompt templates with AI engineers.
• Contribute to testing, debugging, and CI/CD practices; participate in sprint rituals.

Skills

Python

JavaScript/TypeScript

REST APIs

Docker

Kubernetes

CI/CD

OCR/Document processing

LangChain/HuggingFace

React

Git

Tools

Git

Docker

Kubernetes

Job 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 Responsibilities

• 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).

• 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.

• 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.

• 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.

Required Skills & Experience

• 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.

• 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).

  • Experience with parsing, OCR, or document processing libraries is an advantage.

• DevOps & Tools

  • Basic knowledge of CI/CD pipelines, Docker, Git.

  • Familiarity with Kubernetes and cloud/on-prem deployment is a plus.

  • Comfortable working with monitoring/logging tools (Grafana, ELK).

• Soft Skills

  • Willingness to learn quickly and adapt to new technologies.

  • Team player with good communication skills.

  • Problem-solving mindset, able to handle ambiguity and fast iteration.