Role Summary
UltreonAI is an AI Design Studio, at the forefront of designing and deploying custom Agentic AI solutions specifically tailored to enhance the efficiency and competitiveness of Singaporean SMEs. Our mission is to move businesses beyond traditional systems by implementing smart, context-aware AI agents.
This role offers a unique opportunity to be a foundational part of this mission. The Fullstack Developer will play a critical role in owning complete features end-to-end-from user-facing interfaces to backend APIs and AI integration. You will build production-ready AI-powered applications where the frontend, backend, and AI systems work seamlessly together to deliver real business value for our SME clients.
Key Responsibilities
Your primary focus will be on delivering complete, production-ready features that span the entire stack.
- End-to-End Feature Development: Design and build complete features from the ground up-responsive frontend interfaces (dashboards, chat UIs, admin panels) and robust backend APIs that power our AI agents, owning the entire user experience.
- AI Integration: Integrate LLMs (OpenAI, Anthropic, Gemini) into business workflows using frameworks like LangChain or LlamaIndex, building the connective tissue between client applications and AI capabilities.
- Agentic Workflows: Develop logic that allows AI agents to make decisions, execute tools (searching the web, querying databases, sending emails), and handle long-running tasks with proper state management.
- RAG Implementation: Build Retrieval-Augmented Generation (RAG) pipelines that allow AI agents to chat with client data securely, handling document processing, vector storage, and context retrieval.
- Database Management: Design and manage both relational databases (PostgreSQL) for transactional data and vector databases (Pinecone, Weaviate, ChromaDB) for AI semantic search, ensuring data consistency across systems.
- Deployment & Security: Handle deployment of client solutions with proper data sovereignty and security best practices, ensuring distinct deployments per client when required.
Technical Skills & Qualifications
Required Technical Competencies
- Frontend Development: Strong proficiency in React.js and Next.js (App Router, Server/Client Components). Experience building intuitive chat interfaces, real-time dashboards, or analytics interfaces. Comfortable with TypeScript and modern styling approaches (Tailwind CSS).
- Backend Development: Proficiency in Python (FastAPI, Django, or Flask) is essential due to the AI ecosystem's Python-centric nature. Understanding of API design, authentication, async workflows, and webhook handling. Experience with Node.js/TypeScript is a strong bonus.
- AI & LLMs: Hands-on experience working with LLM APIs (OpenAI, Anthropic), prompt engineering, and agentic frameworks like LangChain, LlamaIndex, or similar. Understanding of how to structure prompts, manage context windows, and handle streaming responses.
- RAG Architecture: Practical understanding of Retrieval-Augmented Generation-document chunking, embedding generation, vector similarity search, and context injection into LLM prompts.
- Databases: Experience with SQL (PostgreSQL/MySQL) for relational data modeling and familiarity with Vector Databases (Pinecone, Weaviate, ChromaDB) for semantic search and AI retrieval systems.
- Cloud & Deployment: Familiarity with deploying applications on cloud platforms (Vercel for frontend, AWS/GCP/Azure for backend services). Understanding of Docker/Containerization for consistent deployments.
- Technical Foundations: Proficient with Git/GitHub for version control and comfortable working in a Linux environment.
AI-Specific Full-Stack Patterns
- Streaming Implementations: Building end-to-end streaming pipelines-from LLM API streaming responses through backend websockets/SSE to real-time frontend UI updates.
- Tool/Function Calling: Implementing AI agent tool execution-allowing LLMs to trigger backend functions, query databases, call external APIs, and return structured results.
- Context Management: Managing conversation history, context windows, and memory systems across frontend state, backend storage, and LLM interactions.
Good to Have
- Workflow Automation Tools: Experience with n8n, Zapier, or Make, and understanding how to extend them with custom code nodes or API integrations.
- Local LLMs: Knowledge of deploying and working with local/open-source LLMs (Ollama, HuggingFace models) for privacy-focused or cost-optimized deployments.
- Singapore SME Context: Experience working with Singapore SMEs or B2B SaaS development, understanding common business workflows and pain points.
- Performance Optimization: Experience optimizing both frontend (bundle sizes, lazy loading) and backend (query optimization, caching strategies) for production performance.
Education & Background
- Currently pursuing or recently graduated with a Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related technical field.
Benefits / What You'll Gain
This role is designed to be a high-impact, skill-accelerating experience:
- Full AI Solution Lifecycle Exposure: Gain practical, end-to-end experience building complete AI applications-from UI to backend to AI integration-moving beyond theoretical models to live, production-ready systems serving real businesses.
- In-Demand Technologies: Hands-on work with cutting-edge technologies across the entire stack-Next.js, Python AI frameworks, RAG Architecture, Vector Databases, and LLM API integration-essential skills for the future of AI engineering.
- Real-World Impact: Directly contribute to the success of live Singapore SME projects, building complete features that solve tangible business problems with advanced AI capabilities.
- Ownership & Autonomy: Own entire features from conception to deployment-you're not just a frontend or backend specialist, but responsible for delivering complete, working solutions.
- Mentorship: Direct collaboration and guidance from the Tech Lead, providing insight into full-stack architecture, AI system design, and best practices for building scalable AI-powered applications.
- Versatile Skill Development: Develop T-shaped skills-deep expertise in full-stack development with specialized knowledge in AI integration, making you highly valuable in the AI engineering market.
Application Details
- Work Arrangement: This is a full/part time hybrid working position with flexible working hours. Occasional in-person collaboration in Singapore as needed for key project milestones.
- Probation Period: 6-month probation period to ensure mutual fit and alignment.
- Team Structure: You'll work in project-based teams rather than siloed departments, collaborating closely with other Engineers and taking ownership of complete feature sets.
Join us to build complete AI-powered applications that bring the next generation of business intelligence and Agentic AI to Singapore SMEs!
