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NCS is seeking an AI Engineer to bridge traditional machine learning with Generative AI, building scalable AI solutions for production environments. The role emphasizes Python engineering, model deployment, and collaboration with data engineers and client stakeholders.
You will develop ML models, RAG pipelines, and GenAI applications, while applying rigorous statistical thinking and keeping up with evolving AI tools and best practices.
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.
As an AI Engineer who bridges traditional machine learning and modern generative / agentic AI. This role involves designing, building, and deploying end-to-end AI solutions including classical ML models, RAG-based applications, and lightweight agentic workflows. The successful candidate will contribute hands-on to client delivery projects, applying strong Python engineering and statistical rigour to develop scalable AI solutions that work reliably in production environments.
What will you do?
Design, build, and deploy end-to-end ML models including classification, regression, time-series, and NLP models.
Integrate ML models into production systems and applications.
Monitor model performance and conduct analysis to detect data drift, quality issues, and opportunities for improvement.
Develop GenAI applications including RAG pipelines, prompt-engineered chatbots, and lightweight agentic workflows using frameworks such as LangChain, LlamaIndex, LangGraph, or Python.
Implement effective RAG architectures including chunking strategies, embedding selection, vector store configuration (e.g., Qdrant, Milvus, pgvector), and retrieval evaluation.
Write clean, maintainable, and production-ready Python code.
Participate in code reviews and contribute to shared libraries and internal AI platform components.
Use Git, CI/CD practices, and containerisation tools such as Docker in development workflows.
Work closely with data engineers, MLOps engineers, and client stakeholders to move AI experiments into reliable production deployments.
Document technical approaches, solution designs, and experimental results clearly.
Stay up to date with the evolving AI landscape and introduce relevant tools, techniques, and best practices to the team.
The ideal candidate should possess:
We are driven by our AEIOU beliefs-Adventure, Excellence, Integrity, Ownership, and Unity, and we seek individuals who embody these values in both their professional and personal lives. We are committed to our Impact: Valuing our clients, Growing our people, and Creating our future.
Together, we make the extraordinary happen.
Learn more about us at ncs.co and visit our LinkedIn career site.