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AI Software Delivery Specialist

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Job Description - AI Software Delivery Specialist

Contract Type:

Permanent

Location:

Singapore, Singapore

Date Published:

13-May-2026

Salary:

What You'll Be Doing
  • Review existing codebases to determine where AI-assisted tools can be effectively applied, taking into account architecture, language mix, and code complexity
  • Explore and benchmark AI solutions that support different stages of the engineering lifecycle, such as automated documentation, test creation, and code quality analysis
  • Run practical experiments using AI tools on selected components to assess:
    • Output quality and accuracy
    • Test coverage and completeness
    • Time savings compared to traditional methods
  • Work closely with engineering teams to:
    • Identify suitable candidates for pilot initiatives
    • Validate AI-generated outputs
    • Feed insights into broader engineering practices
  • Contribute to the rollout of AI-enabled engineering practices, including:
    • Defining success criteria
    • Establishing guardrails and review processes
    • Highlighting cost-benefit trade-offs
  • Investigate how AI capabilities can be embedded into existing development workflows and delivery pipelines
  • Evaluate how ready the organization is to adopt AI-driven practices, and communicate findings to both technical and non-technical stakeholders
What We're Looking For
Core Experience
  • Solid background in software engineering (typically 6+ years)
  • Practical exposure to AI-powered development tools in a professional setting
  • Experience assessing and trialing new technologies in structured environments, with clear evaluation criteria
  • Familiarity with applying AI to:
    • Generate or enhance technical documentation
    • Support automated testing efforts
  • Strong understanding of software delivery practices and where automation can add value without compromising quality
  • Working knowledge of unit testing approaches and frameworks across common stacks (e.g., .NET or JavaScript ecosystems)
  • Ability to balance technical possibilities with real-world constraints such as team maturity and operating models
  • Confident communicator, able to translate technical findings into meaningful insights for stakeholders
  • Awareness of considerations around data usage, security, and intellectual property when leveraging AI tools
Additional Advantage
  • Exposure to large language model (LLM) use cases in engineering, such as code interpretation or rules extraction
  • Experience working with modern front-end frameworks or full-stack environments
  • Familiarity with tools that assist in automated code review or quality checks
  • Background in enterprise-grade platforms or ecosystems (e.g., Microsoft stack)
  • Understanding of prompt design and optimisation for technical use cases
  • Experience with behaviour-driven or acceptance-driven testing approaches
  • Awareness of techniques that improve AI context handling (e.g., retrieval-based approaches)
  • Exposure to vendor/tool evaluation from a security or compliance standpoint
  • Contributions to internal or external knowledge sharing on AI in engineering
ST
Reg No. R1768414
BeathChapman Pte Ltd
Licence no. 16S8112

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