#EG AI Engineer (Contact Centre)

NCS; Singapore; On-site; SGD 70,000 - 120,000; Full time

Benefits offered by this job

Competitive compensation

Professional development support

AEIOU values in the workplace

Job summary

NCS is an AI Tech Services leader in Asia Pacific with a strong Singtel backing, delivering AI-driven platforms across industries from Singapore. We seek an AI Engineer who blends traditional ML with generative/agentic AI, developing end-to-end solutions for clients and contributing to production-grade pipelines.

Design and deploy ML models, integrate them into production systems, and collaborate with data engineers and stakeholders to scale AI experiments into reliable deployments.

Qualifications

• 2-5 years hands-on AI/ML engineering or data science experience.
• Delivered 2-3 ML projects in production or near-production.
• Strong Python programming with Pandas, NumPy, Scikit-learn and PyTorch or TensorFlow.
• Solid ML fundamentals: feature engineering, model evaluation, bias-variance trade-off, hyperparameter tuning.
• Hands-on with RAG chatbots and LLM APIs (OpenAI/Azure AWS Bedrock).
• Experience with vector stores and retrieval quality evaluation.
• Experience with at least one cloud platform (AWS/Azure/GCP).
• Git, CI/CD and Docker proficiency.

Responsibilities

• 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 detect data drift and quality issues.
• Develop GenAI applications including RAG pipelines, chatbots, and agentic workflows.
• Implement RAG architectures with chunking, embeddings, and vector stores.
• Write clean, production-ready Python code; participate in code reviews and contribute to libraries.
• Collaborate with data engineers, MLOps, and client stakeholders to move experiments to production deployments.

Skills

Python

Pandas

NumPy

Scikit-learn

PyTorch

TensorFlow

RAG chatbots

LLM APIs

Git

CI/CD

Docker

MLOps

AWS

Azure

GCP

Education

B.Sc. in Computer Science

MSc in ML/AI

Tools

LangChain

LlamaIndex

Qdrant

Milvus

pgvector

Airflow

ZenML

Weights & Biases

Job 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

As anAI 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 rigor 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.

Generative AI & RAG Application Development

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.

Software Engineering & Development Practices

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.

Qualifications

The ideal candidate should possess:

• 2-5 years of hands-on experience in AI/ML engineering or data science roles
• Demonstrable track record of delivering at least 2-3 ML projects (beyond notebooks - production or near-production) and 1-2 GenAI / agentic AI projects
• Strong Python programming skills including Pandas, NumPy, Scikit-learn, and PyTorch or TensorFlow
• Solid understanding of machine learning fundamentals including feature engineering, model evaluation, bias-variance trade-off, and hyperparameter optimisation
• Hands-on experience building RAG chatbots and applications using LLM APIs such as OpenAI, Anthropic, AWS Bedrock, Azure OpenAI, or equivalent
• Working knowledge of RAG architecture decisions including chunking strategies, embedding model selection, vector store configuration, and retrieval quality evaluation
• Practical experience with at least one vector database such as Qdrant, Milvus, pgvector, or equivalent
• Experience with at least one cloud platform such as AWS, Azure, or GCP for model training or deployment
• Proficiency with Git, CI/CD basics, and containerisation (Docker)

Preferred Skills:

• Experience building voice AI bots using a pro-code approach such as Twilio, Amazon Connect, Deepgram, Whisper + TTS pipelines
• Exposure to agentic patterns such as tool-calling agents, ReAct loops, multi-step planning, or reflection mechanisms
• Familiarity with MLOps tooling such as MLflow, Weights & Biases (W&B), model registries, or orchestration tools like Airflow, Prefect, or ZenML
• Experience with evaluation frameworks for RAG and GenAI outputs such as RAGAS, DeepEval, or promptfoo
• Knowledge of responsible AI principles including bias detection, fairness metrics, and output guardrails
• Exposure to NLP pipelines including entity extraction, text classification, and summarisation
• Prior experience in a systems integrator (SI), consultancy, or multi-client delivery environment
  

Additional Information

Why Join NCS

Lead high-impact Data & AI advisory programs for major enterprises and public sector clients.

Shape enterprise strategies and governance frameworks that drive real transformation.

Work with a talented, multidisciplinary team in a collaborative environment.

Competitive compensation and strong professional development support.

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.