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Staff Engineer - AI Data Engineering

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Staff Engineer - AI Data Engineering in Others new

  • Prudential plc
  • Full time
  • Email
  • Singapore, Singapore

Responsibilities

  • Define enterprise AI Data Engineering strategy, architecture, engineering standards, and reusable architectural patterns.
  • Design and lead scalable data platforms supporting AI/ML, GenAI, LLM, analytics, and enterprise data products.
  • Build ingestion and transformation frameworks for databases, APIs, documents, events, logs, and enterprise applications.
  • Establish batch, near-real-time, and streaming data pipelines with automated validation, quality controls, metadata management, and lineage.
  • Lead RAG, document ingestion, parsing, chunking, enrichment, embedding, vector search, semantic retrieval, reranking, and enterprise knowledge repository capabilities.
  • Create data pipelines for LLM evaluation, AI grounding, authorized retrieval, applicable fine-tuning, and AI agents.
  • Provide technical leadership across ETL/ELT, distributed processing, lakehouse and warehouse architectures, event-driven design, data APIs, and data services.
  • Embed Infrastructure-as-Code, CI/CD, DevOps, DataOps, observability, reliability, and developer productivity practices.
  • Implement governance, privacy, security, access controls, traceability, auditability, and Responsible AI practices for AI data pipelines.
  • Define data quality standards and monitor freshness, completeness, accuracy, schema changes, pipeline failures, SLAs, and SLOs.
  • Lead and mentor senior data engineers, AI engineers, and platform engineers across multiple squads and programs.
  • Conduct architecture and engineering design reviews, resolve complex technical issues, and partner with architecture, cloud, cybersecurity, data, AI/ML, and application engineering teams.

Requirements

  • 15+ years of overall technology and engineering experience with substantial depth in data engineering, data platforms, or related disciplines.
  • Significant experience leading enterprise-scale data engineering programs and teams.
  • Strong experience designing and implementing cloud-native data platforms and distributed data-processing architectures.
  • Demonstrated experience supporting AI/ML or GenAI workloads through data engineering and processing structured and unstructured data.
  • Experience with enterprise-grade security, governance, privacy, data quality, lineage, and regulatory practices, including sensitive or PII data.
  • Strong coding capability in Python, SQL, and PySpark or equivalent technologies.
  • Experience with CI/CD, DevOps, DataOps, automated engineering practices, observability, and reliability.
  • Proven ability to operate across architecture, engineering, and senior stakeholder environments.
  • Experience with GenAI and LLM solutions, RAG architectures, vector databases, embedding pipelines, semantic or hybrid search, knowledge graphs, AI agents, feature stores, MLOps or LLMOps, evaluation datasets, unstructured-document processing, or Responsible AI is preferred.
  • Bachelor’s or master’s degree in Computer Science, Data Engineering, Software Engineering, Information Technology, or a related discipline.
  • Relevant Microsoft Azure, Databricks, or equivalent cloud/data certifications are desirable; advanced AI/ML, Data Engineering, or Cloud Architecture certifications are advantageous.

Prudential plc

Prudential plc provides life and health insurance and asset management for consumers across Asia and Africa, including through its Eastspring Investments arm. The public company is headquartered in Hong Kong with dual primary listings in Hong Kong and London, and traces its origins to 1848 in the...

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