#EG AI Engineer (Contact Centre)

NCS Group; Singapore; On-site; SGD 60,000 - 90,000; Full time

Benefits offered by this job

Competitive compensation

Professional development support

Collaborative work environment

Job summary

NCS Group in Singapore is seeking an AI Engineer to design, build, and deploy AI solutions, focusing on both traditional ML and emergent generative AI technologies. The ideal candidate will have solid experience in AI/ML engineering, especially in developing ML models and applications.

This role offers the chance to work closely with a talented team in a dynamic environment while contributing to impactful AI projects across various industries. Applicants should have a degree in a relevant field, coupled with strong programming skills in Python.

Qualifications

• 2–5 years of hands-on experience in AI/ML engineering or data science roles.
• Track record of delivering at least 2–3 ML projects beyond notebooks.
• Strong Python programming skills including Pandas, NumPy, Scikit-learn.

Responsibilities

• Design, build, and deploy end-to-end ML models.
• Develop GenAI applications including RAG pipelines and chatbots.
• Work closely with data engineers and MLOps engineers.

Skills

Python programming

ML model development

AI/ML engineering

Data science

CI/CD practices

Education

Degree in Statistics, Mathematics, Computer Science, or related field

Tools

Pandas

NumPy

Scikit-learn

PyTorch

TensorFlow

Docker

Git

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 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 rigor to develop scalable AI solutions that work reliably in production environments.

AI / ML Model Development & Deployment

• 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.

Collaboration & Delivery

• 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.

Research & Innovation

• 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)
• Ability to read and write at least one additional programming language such as TypeScript/JavaScript, Java, Go, or advanced SQL
• Degree in Statistics, Mathematics, Computer Science, Data Science, or a closely related quantitative discipline

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

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.