AI Engineer – Generative AI / Azure
Must-have:PythonGitAzureBackendDataCI/CDAISecurityJunior
About the company
We are looking for a hands-on AI Engineer to join a growing AI engineering team within a leading financial-services organisation in Singapore.
Your tasks
You will design, build and deploy Generative AI and LLM-powered applications within a Microsoft Azure environment, helping move AI solutions from prototype through to production.
- Build GenAI, LLM and RAG-based applications using Azure.
- Develop AI assistants, copilots and agentic AI workflows.
- Integrate AI applications with enterprise data, APIs and internal systems.
- Develop backend services and APIs primarily using Python.
- Work with Azure AI Search, Microsoft Fabric and related Azure services.
- Support model testing, evaluation, monitoring and production deployment.
- Build AI solutions that meet financial-services security, risk and governance standards.
- Partner with Architecture, Data, Engineering and business teams to deliver practical AI use cases.
This is an opportunity to help build an internal AI engineering capability, working on solutions across front-office productivity, research, knowledge management, operations, risk and compliance.
Requirements
- 2–5 years' experience in Software Engineering, AI/ML Engineering, Data Engineering or a related area.
- Strong hands-on Python development skills.
- Experience working within a Microsoft Azure environment.
- Practical exposure to Generative AI, LLMs and RAG.
- Experience with APIs, Git/GitHub and SQL.
- Exposure to Azure OpenAI / Microsoft Foundry, Azure AI Search, Microsoft Fabric or similar technologies is highly desirable.
- Knowledge of AI agents, vector search, embeddings, CI/CD or containers would be advantageous.
- Financial-services experience is beneficial but not essential.
We're particularly interested in hands-on engineers who enjoy building and deploying real-world AI applications, rather than purely research or strategy-focused profiles.
Other
Location: Singapore | Junior to Mid-Level