Senior AI Developer
- Singapore
- Permanent
- Full-time
- Execute application development deliverables and activities
- Design, develop, and deploy scalable AI/ML/DL models using state-of-the-art techniques.
- Build, fine-tune, and operationalize LLMs and Agentic AI systems for enterprise-grade applications.
- Leverage Azure OpenAI and other cloud-native services to implement advanced AI capabilities.
- Collaborate with data engineers to ensure seamless data pipeline integration and model deployment.
- Implement robust MLOps/DevOps practices for continuous integration, delivery, and monitoring of AI models.
- Translate complex business requirements into technical solutions in collaboration with cross-functional teams.
- Optimize model performance for scalability, reliability, and production-readiness.
- Stay abreast of the latest advancements in AI, ML, and cloud technologies, and apply them to real-world problems.
- Participate in various phases of the Software Development Life Cycle (SDLC) for IT Projects and to interface with various IT stakeholders such as 3rd party vendor suppliers, business analysts and project managers to perform development activities
- Documenting the application and database design
- Conducting Peer code reviews and Unit Testing
- Work closely with the Application Development team and QA teams to ensure any defects highlighted in QA or UAT phases are remediated.
- Adhere to SDLC, and Project Governance internal and regulatory (Sarbanes Oxley & Gaming Regulatory Authority) guidelines, policies, and procedures.
- Bachelor’s / Master’s degree in Computer Science, Information Technology, or related field.
- Minimum 5 years of hands-on experience in AI/ML/DL development, with a strong focus on Deep Learning and Generative AI.
- Proficient in Python, PyTorch/TensorFlow, Apache Spark, and SQL.
- Experience in one or more OSS frameworks for ML ops like Kubeflow / MLFlow
- Demonstrated experience with Azure AI services, particularly Azure OpenAI and Azure Machine Learning.
- Exposure to data engineering tools and concepts (e.g., Azure Data Factory, Delta Lake).
- Hands-on experience with modern Generative AI architectures, including Agentic AI frameworks (e.g., LangChain, LangGraph, MCP, Semantic Kernel), and Retrieval-Augmented Generation (RAG) pipelines leveraging vector databases and advanced prompt engineering techniques.
- Experience delivering solutions using both agile and waterfall methodologies in fast-paced environments.
- Solid understanding of DevOps and MLOps practices, including tools such as GitHub Actions, Azure DevOps, MLflow, and version control systems, with additional familiarity in DevSecOps approaches for embedding security into the development and deployment lifecycle.
- Strong communication skills with the ability to engage diverse stakeholders and demonstrate proactiveness.