Jobfoundry
Jobfoundry
Keppel

Manager, Data & Digital

Keppel
Advanced Manufacturing & ElectronicsSingaporeFull-time3 days ago
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About the role

AI summarised

This is a senior full-stack software engineering role at a technology company, focused on building AI-powered data solutions. The engineer will architect end-to-end UI-to-data pipelines, integrate AI platforms, and implement cloud-native systems using AWS and modern frontend frameworks.

IndustrialFull-timeGeneral

Key Responsibilities

  • Architect, build, and deploy production-ready full-stack systems, including data pipelines, automated tools, and multimodal document processing solutions.
  • Develop modern, responsive user interfaces using React, TypeScript, and/or other modern scripting languages.
  • Build robust backend APIs and services that integrate AI platforms with enterprise applications.
  • Build and operate scalable, serverless architectures using AWS services (e.g., Lambda, ECS, API Gateway, S3, DynamoDB).
  • Integrate applications with organizational AI platforms and external AI services, including inference endpoints and agent-based systems.
  • Implement orchestration patterns for multi-agent workflows and AI-driven automations.
  • Implement comprehensive full-stack observability, including monitoring of performance, latency, token usage, and cost.
  • Design and maintain CI/CD pipelines with automated testing, quality gates, and deployment strategies.
  • Contribute to architectural decisions, coding standards, and engineering best practices.
  • Promote effective code sharing, versioning, documentation, and cross-team collaboration.

Requirements

  • 5–6 years of professional experience in full-stack software engineering delivering enterprise-grade applications to production.
  • Strong proficiency in Python for backend and AI-integrated services.
  • Hands-on experience with React, TypeScript, and/or similar modern scripting languages.
  • Familiarity with modern frontend and UI ecosystems (e.g., Next.js, micro-frontends, agent-driven UI frameworks).
  • Strong hands-on experience with AWS, including services such as Bedrock, EC2, S3, CloudFront, and Lambda.
  • Experience with Docker and containerized workloads.
  • Solid understanding of CI/CD automation using tools such as GitHub Actions, Fastlane, or equivalent.
  • Experience working with relational databases, vector databases, and hybrid search approaches.
  • Exposure to multimodal AI models and services for document, image, and diagram extraction.
  • Familiarity with AI/ML service integration in production environments.