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GovTech Singapore

Principal Software Engineer, Engineering Effectiveness, Software Engineering Practice

GovTech Singapore is hiring a Principal Software Engineer, Engineering Effectiveness, Software Engineering Practice in Singapore, Singapore. Level rates it ; you can apply on GovTech Singapore.

Level's read on this job

  • Level rates this software engineer role Works on AI ●●●○: the daily work is on AI products, without building the model.
  • Tools and skills the posting cites include AI agents.
  • Level classifies it as a lead role.
  • Level lists 257 other open roles at GovTech Singapore.

AI in this role

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GovTech is the lead agency driving Singapore’s Smart Nation initiatives and public sector digital transformation. As the Centre of Excellence for Infocomm Technology and Smart Systems (ICT & SS), GovTech develops the Singapore Government’s capabilities in Data Science & Artificial Intelligence, Application Development, Smart City Technology, Digital Infrastructure, and Cybersecurity.  
 
At GovTech, we offer you a purposeful career to make lives better where we empower our people to master their craft through robust learning and development opportunities all year round. 
 
Play a part in Singapore’s vision to build a Smart Nation and embark on your meaningful journey to build tech for public good. Join us to advance our mission and shape your future with us today!  
 
Learn more about GovTech at tech.gov.sg. 

 

[What you will be working on] At GovTech, you can build technology that improves public services while developing your craft alongside engineers working across a wide range of public-sector systems.

The GovTech Software Engineering Practice improves how software is built, tested, shipped and maintained across the Government. We develop shared engineering standards and capabilities, support their adoption, and use evidence to understand whether they are improving outcomes.

The Practice is organised around a small number of pillars, each led by a Principal Engineer. This role leads a new Engineering Effectiveness Measurement pillar. You will bring together and extend measurement capabilities that already exist within the Software Engineering Practice and partner teams. You will establish a coherent approach to measuring developer experience, engineering capability and delivery outcomes, then turn that evidence into practical decisions about platforms, tools and ways of working.

You will align existing data, analytics and research capabilities, identify important gaps, and extend them where needed. You will set the pillar’s direction and priorities, provide technical leadership to engineers contributing to its work, and influence senior leaders across organisational boundaries.

Our north star is to:

Give engineering leaders a trustworthy view of how effectively their teams can deliver, where the most important constraints lie, and which changes are most likely to help.

In your first 12 months, you will establish a trusted baseline of engineering effectiveness measurement, roll out an engineering maturity framework across GovTech and partner agencies, and help engineering leaders act on the most important constraints affecting their teams.

As the tech lead for Engineering Effectiveness Measurement pillar, you will:

Align and extend our measurement capability

  • Bring together the data, instrumentation, analytics and research capabilities that already exist within the Software Engineering Practice and partner teams. Establish a coherent measurement approach, address important gaps and extend the capability where needed.
  • Combine delivery data, platform signals, surveys and qualitative research to understand developer experience, engineering capability and delivery outcomes without reducing effectiveness to a single metric.

Run developer experience research

  • Design, run and interpret developer experience surveys, structured interviews and field research. Use quantitative and qualitative methods together to understand what helps engineering teams deliver and what gets in their way.

Measure and improve engineering maturity

  • Lead the development and rollout of an engineering maturity framework across GovTech and partner agencies. Work with platform teams and engineering leaders to build on existing data and analytics, define useful indicators of engineering capability, maturity and platform adoption, and identify where additional evidence is needed.
  • Use software catalogue, platform, delivery and research data to help teams understand their current position, identify practical improvements and track progress over time. Ensure the framework supports learning and improvement rather than becoming a compliance exercise or a simplistic ranking of teams.

Evaluate the impact of AI engineering

  • Work with other Practice pillars and engineering teams to assess how AI coding tools and agentic workflows affect developer experience, software quality and delivery outcomes. Design evaluations that separate meaningful improvements from novelty, selection effects and noise.

Turn evidence into decisions

  • Translate findings into clear recommendations for the Practice, senior engineering leaders and engineering leads across GovTech’s delivery organisations. Help them decide where to invest, which constraints to address and whether interventions are producing the intended results.

Turn findings into improvements

  • Work with platform and engineering teams to translate findings into changes to tools, standards and ways of working. Where a lightweight prototype can test an idea or close an immediate gap, build it yourself. This might include a dashboard, research pipeline or platform integration.

Collaborate across the Practice

  • Work as a peer with other pillar leads and partner teams. Ensure the maturity framework and wider measurement work reflect what teams are building and experiencing. Feed the resulting evidence into platform, tooling and Practice roadmaps.

Develop capability across GovTech

  • Build measurement and research capability across the Practice and the wider GovTech engineering community. Mentor engineers, share practical methods and represent the Practice credibly with senior technical and organisational leaders.

[What we are looking for] 

You may be a strong fit if you have:

  • Substantial experience in software engineering, engineering data, developer experience, engineering effectiveness or a closely related discipline. We care more about the combination of capabilities than the path you took to develop them.
  • Experience designing measurement approaches for complex technical or organisational systems.
  • Strong quantitative skills, including working with metrics, analytics, statistics and dashboards.
  • Experience with qualitative research methods, such as interviews, surveys and research synthesis, and sound judgement about when to use each method.
  • A thoughtful understanding of engineering measurement frameworks such as DORA and SPACE, including their limitations and the contexts in which they are useful.
  • Sound judgement about privacy, incentives and the unintended consequences of measurement.
  • The ability to turn incomplete or contested evidence into a clear narrative while being transparent about uncertainty and limitations.
  • Experience operating as a Principal-level individual contributor, setting technical direction, doing substantial technical and analytical work, and influencing without direct authority.
  • A record of working across organisational boundaries and building shared ownership with engineering, platform, data and leadership teams.
  • A focus on outcomes. You understand that a survey, scorecard or dashboard has value only if it improves a decision or leads to a useful change.

Experience in any of the following would be valuable:

  • Establishing or leading a developer experience, productivity or engineering effectiveness function.
  • Developing and rolling out an engineering maturity framework across multiple teams or organisations.
  • Designing and analysing large-scale developer surveys or other structured research programmes.
  • Building maturity models or scorecards using data from internal developer platforms, software catalogues or tools such as Backstage.
  • Running structured interviews or field research with engineering teams.
  • Evaluating the effects of developer tools, AI-assisted engineering or changes to software delivery practices.
  • Building analytics products, research pipelines or lightweight internal tools.
  • Turning ambiguous questions, such as whether an engineering investment has improved effectiveness, into defensible and useful findings.
  • Working across a large or federated engineering organisation.

What we offer you:   

GovTech is an equal opportunity employer committed to fostering an inclusive workplace that values diverse voices and perspectives, as we believe that diversity is the foundation to innovation.    

Our employee benefits are based on a total rewards approach, offering a holistic and market-competitive suite of perks. These include leave benefits to meet your work-life needs and employee wellness programs.  

We champion flexible work arrangements (subject to your job role) and trust that you will manage your own time to deliver your best, wherever you are, and whatever works best for you.   

 

Learn more about life inside GovTech at go.gov.sg/GovTechCareers. 
Stay connected with us on social media at go.gov.sg/ConnectWithGovTech

How we rate this

Principal Software Engineer, Engineering Effectiveness, Software Engineering Practice at GovTech Singapore rates 64 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

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Skills and AI tools this role asks for

AI agents

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Pay

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$167k

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  2. Describe a typical day in a role like this one: which parts run through AI directly?
  3. If you removed AI from this role, what would be left, and how do you decide what still needs a human?

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  • List these exact terms on your resume: AI agents. An applicant tracking system matches the wording, not the idea.
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