AI Engineer (Contact Centre)

About the role

NCS, an AI tech services company and subsidiary of the Singtel Group, is hiring an AI Engineer in Singapore. The role bridges traditional machine learning and modern generative and agentic AI, designing, building and deploying end-to-end AI solutions including classical ML models, RAG-based applications and lightweight agentic workflows. You will contribute hands-on to client delivery projects, applying strong Python engineering and statistical rigor to scalable, production-ready AI solutions.

Key responsibilities

• Design, build and deploy ML models (classification, regression, time-series, NLP) and integrate them into production systems, monitoring performance and detecting data drift.
• Build GenAI applications such as RAG pipelines, prompt-engineered chatbots and agentic workflows using LangChain, LlamaIndex, LangGraph or Python, with chunking, embedding selection and vector store configuration.
• Write clean, maintainable Python code, take part in code reviews, use Git, CI/CD and Docker, and share libraries and internal AI platform components.
• Collaborate with data engineers, MLOps engineers and client stakeholders to move AI experiments into production, and document technical approaches and results.
• Stay up to date with the AI landscape and bring new tools and best practices to the team.

Required profile

• 2-5 years of hands-on experience in AI/ML engineering or data science roles.
• Track record of 2-3 ML projects beyond notebooks and 1-2 GenAI/agentic AI projects.
• Experience building RAG chatbots with LLM APIs such as OpenAI, Anthropic, AWS Bedrock or Azure OpenAI.
• Ability to read and write at least one other language such as TypeScript/JavaScript, Java, Go or advanced SQL.
• Preferred: voice AI bot experience, agentic patterns, MLOps tooling, RAG evaluation frameworks, responsible AI principles, NLP pipelines, and prior work in a systems integrator or multi-client delivery environment.

Required skills

• Python, Pandas, NumPy, Scikit-learn, PyTorch or TensorFlow
• RAG architecture and vector databases such as Qdrant, Milvus or pgvector
• AWS, Azure or GCP for model training or deployment
• Git, CI/CD basics and Docker

NCS offers competitive compensation, professional development support and the chance to lead high-impact data and AI advisory programs for major clients. Official communications come only from verified NCS email addresses.