#EG Fullstack Developer – AI Applications
- Compensation
- Not disclosed
- Location
- Singapore
- Work setup
- Onsite
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 2+ years
- Category
- Fullstack
- Posted
Skills
Must have
- Strong in ReactJS, basic state management (Context, Redux, or simple React Query), and TypeScript.
- Strong Python development experience (FastAPI/Flask).
- Experience with REST APIs, JSON, and async handling.
- Hands-on experience with at least one major cloud AI service (AWS Bedrock, Azure AI Foundry, or Google Vertex AI), including model integration, orchestration, and prompt handling.
- Working knowledge of China-origin models (DeepSeek, Qwen, GLM) a plus.
- Familiarity with agentic orchestration frameworks such as AWS Strands or LangGraph, for implementing multi-step agent workflows.
- Familiar with file upload handling (PDF, DOCX, text).
- Containerization experience (Docker) and deployment to at least one major cloud's container/serverless services; familiarity with Kubernetes (EKS/AKS/GKE) is a plus.
- Familiarity with Postgres schema design, querying, and managed database setup.
- Comfortable building lightweight RAG and agentic pipelines and integrating with vector stores.
- Understand how Gen AI and agentic outputs can vary and need dynamic rendering.
- Working knowledge of secure coding practices and code scanning tools.
Nice to have
- Experience with OpenSearch Serverless, Azure AI Search, or other vector databases.
- Familiarity with event-driven architectures (SQS/SNS/EventBridge or Azure/GCP equivalents).
- Basic knowledge of prompt engineering and Gen AI output evaluation.
- Exposure to infrastructure-as-code tools (Terraform).
- Exposure to Singapore Government GCC/HCC environments.
Full description
Company Description
NCS is a leading AI Tech Services company. With a 15,000-strong team across the Asia Pacific, NCS scales its platforms and capabilities to provide clients with greater agility and AI expertise across a range of Industries. Embracing a strong ecosystem of global partners, NCS transforms technology services delivery combining AI with digital resilience to drive real business impact. NCS is a subsidiary of the Singtel Group.
Job Description
This role sits within NCS AI Central's (AIC) Forward Deployed Engineering (FDE) model — the combined capability that takes AI solutions from proof-of-concept through to hardened production systems. As Fullstack Developer, you build both the frontend and backend of Gen AI applications — from UI through API and cloud deployment — operating across both fast-moving FDE engagements (POC/POV, pilot deployments) and steady-state system development and maintenance work.
What will you do:1. Frontend Development
- Build a simple, clean UI to support key POC and application workflows (upload, query, view results), using ReactJS.
- Implement screens with usable UX, optimised for performance and cross-device compatibility.
- Integrate with backend APIs for model inference, RAG results, and agentic workflow status and outputs.
- Handle user inputs, file uploads, and display model/agent outputs responsively — accounting for the multi-step, non-deterministic nature of agentic workflows.
- Add lightweight feedback/error handling for API failures or delayed responses; implement basic authentication or access control where required.
2. Backend Development
- Design and develop backend services and APIs using Python (FastAPI/Flask) to support Gen AI functionality.
- Implement endpoints for model inference requests, RAG workflows, agentic workflow orchestration (e.g. using frameworks such as AWS Strands or LangGraph), and document upload/processing/storage.
- Integrate with cloud AI services for inference and model orchestration — AWS Bedrock, Azure AI Foundry, or Google Vertex AI depending on the engagement — including China-origin models (DeepSeek, Qwen, GLM) where self-hosted or exposed via compatible endpoints. Build lightweight pipelines for RAG (chunking, embeddings, retrieval).
- Apply LLMOps practices to support model monitoring and versioning as applications mature toward production.
- Manage data storage using Postgres (RDS or equivalent) and/or vector search services (OpenSearch, FAISS, or cloud-native equivalents).
3. Deployment & Quality
- Containerise applications using Docker and deploy to AWS ECS Fargate/Lambda, Azure Container Apps/Functions, GCP Cloud Run, or equivalent Kubernetes-based services (EKS/AKS/GKE) where required.