AI/ML Engineer (Agentic AI & Data Science) – 12-Month Contract | Banking Client | MBFC

NTT SINGAPORE PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

NTT Singapore Pte. Ltd. seeks an AI/ML Engineer (Agentic AI & Data Science) for a 12-month contract to design, develop and deploy AI solutions for a banking client.

You will work on Agentic AI platforms, RAG, embeddings, vector search, and production-grade REST APIs. Collaboration with stakeholders, data scientists and software engineers is essential. The role covers generative AI, knowledge management, and automation for market intelligence and client engagement.

Qualifications

• Hands-on experience building and deploying AI or ML solutions into production.
• Strong Python programming with practical SQL and REST API experience.
• Experience with Scikit-learn, XGBoost/LightGBM, and TensorFlow or PyTorch.

Responsibilities

• Design and develop AI agents using Dify and Agentic AI frameworks.
• Build and optimise RAG solutions with document ingestion, embeddings, vector search and retrieval.
• Develop agent orchestration workflows and integrate tools, APIs and enterprise data sources.
• Implement prompt engineering, evaluation, memory and state management.
• Deploy production-ready AI services and REST APIs using Python and CI/CD pipelines.

Skills

Python programming

SQL

REST APIs

Generative AI

LLM applications

Data Science

Stakeholder communication

Tools

OpenShift/OCP

Docker

Kubernetes

Git

TensorFlow

PyTorch

Job description

AI/ML Engineer (Agentic AI & Data Science) – 12-Month Contract | Banking Client | MBFC

Employer: NTT Singapore Pte. Ltd.
Employment Type: 12-month contract, renewable subject to performance and business requirements.
Work Location: MBFC , Singapore
Client Industry: Banking / Financial Services

About the Role

We are seeking an AI/ML Engineer with strong Data Science and Generative AI capabilities to design, develop and deploy AI solutions supporting a banking client’s Global Financial Markets business.

The role covers Agentic AI platforms, recommendation engines, retrieval systems and predictive models for market intelligence, product recommendations, client engagement, workflow automation and knowledge management.

You will collaborate with business stakeholders, product owners, data scientists and software engineers to deliver scalable, production-ready AI solutions.

Key Responsibilities

Generative AI and Agentic AI

• Design and develop AI agents using Dify and modern Agentic AI frameworks.
• Build and optimise RAG solutions, including document ingestion, embeddings, vector search, retrieval and reranking.
• Develop agent orchestration workflows and integrate tools, APIs and enterprise data sources.
• Implement prompt engineering, evaluation, reflection, memory and state management.
• Develop reusable AI components for multiple business use cases.

Machine Learning and Data Science

• Develop models for client propensity prediction, recommendations, classification, ranking, behavioural analytics and next-best-action recommendations.
• Perform exploratory data analysis, feature engineering, model training and evaluation.
• Analyse structured and unstructured datasets to generate actionable business insights.
• Monitor model performance and improve accuracy, relevance and reliability.

Application Development and Deployment

• Build production-ready AI services and REST APIs using Python.
• Integrate AI applications with enterprise systems and knowledge repositories.
• Develop data pipelines, transformations and data quality controls.
• Deploy and operate AI services using OpenShift/OCP, Docker and Kubernetes.
• Implement CI/CD pipelines, monitoring, observability and evaluation frameworks.
• Optimise performance, scalability and infrastructure costs.
• Maintain technical documentation and collaborate with stakeholders throughout delivery.

Required Qualifications and Experience

• Relevant experience in AI Engineering, Machine Learning Engineering, Data Science or Advanced Analytics.
• Hands-on experience building and deploying AI or ML solutions into production.
• Strong Python programming skills, with practical SQL and REST API experience.
• Experience with Scikit-learn, XGBoost/LightGBM, and TensorFlow or PyTorch.
• Hands-on experience in all five mandatory Generative AI areas: RAG, vector search, LLM applications, Dify and Agentic AI frameworks.
• Knowledge of data pipelines, data transformation, feature engineering and data quality management.
• Experience with OpenShift/OCP, Docker, Kubernetes, CI/CD pipelines and Git.
• Ability to translate business requirements into technical solutions and communicate clearly with business and engineering teams.

Preferred Experience

• Banking, financial services, capital markets or wealth management.
• Recommendation engines, personalisation and next-best-action solutions.
• Search, retrieval and enterprise knowledge management platforms.
• MLOps, LLMOps and AI governance.
• Unstructured document repositories and enterprise knowledge sources.