jobs in Prudential Services Singapore Pte Ltd

Prudential Services Singapore Pte Ltd Hiring! Full Time AI Engineering Lead in - Ricebowl

AI Engineering Lead

Prudential Services Singapore Pte Ltd

Undisclosed

Singapore

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Working Location

  • Singapore

Job Description

Responsibilities

We are seeking an AI Engineer to join the DPS Engineering team, embedded within a cross-functional product delivery squad. This role will focus on designing, building, and deploying AI-driven capabilities that enhance product features, improve operational efficiency, and support data-driven decision-making.


The individual will work closely with product managers, engineers, and domain experts to translate business requirements into scalable AI solutions, ensuring seamless integration into production systems.


1. AI Solution Development

  • Design, develop, and deploy machine learning and AI models (e.g., NLP, predictive analytics, GenAI use cases) aligned with product objectives
  • Translate business problems into AI/ML solutions with clear success metrics


2. Product Integration

  • Embed AI capabilities into product features and workflows within the delivery squad
  • Collaborate with backend/frontend engineers to ensure scalable and reliable deployment


3. Model Lifecycle Management

  • Build and maintain end-to-end ML pipelines (data ingestion, training, evaluation, deployment, monitoring)
  • Ensure continuous improvement through model retraining and performance tuning


4. Data & Engineering Collaboration

  • Work with data engineers to define data requirements, pipelines, and data quality standards
  • Ensure proper feature engineering and dataset governance


5. Risk, Governance & Responsible AI

  • Ensure AI solutions comply with enterprise standards on security, privacy, and responsible AI usage
  • Document models, assumptions, and limitations clearly


Requirements:

  • Strong experience in Python and AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
  • Experience with GenAI / LLMs (e.g., prompt engineering, RAG architectures, API-based models)
  • Familiarity with MLOps practices (CI/CD, model deployment, monitoring)
  • Experience working with cloud platforms (Azure preferred, AWS/GCP acceptable)
  • Knowledge of data engineering concepts (SQL, data pipelines, APIs)
  • Proven track record of delivering AI solutions in production environments
  • Experience working in agile, squad-based delivery models
  • Strong problem-solving mindset with a focus on business impact
  • Ability to work in fast-paced, iterative delivery environments
  • Effective collaboration across engineering, product, and business teams
  • Curiosity and drive to continuously learn emerging AI technologies

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