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Newbridge, a Singapore-based enterprise, seeks a Principal-level engineer to define how AI augments software delivery at scale. You will set SDLC standards for AI usage, build self-serve platforms, and stay hands-on across architecture and code with live squads.
You will influence senior stakeholders, mentor tech leads, and drive adoption of modern quality engineering across distributed cloud-native systems. This is a strategic builder role with tangible impact.
We are working with one of Singapore's most established large-scale enterprises. With operations across Asia Pacific and responsibility for systems that power essential national services, they are investing heavily in a Digital, Data and AI-led transformation.
The central Digital Engineering group sits at the core of this shift – responsible for the architecture and operation of large, complex, always-on platforms.
This is where you come in.
This is a newly created Principal-level role to answer a fundamental question: how should great engineering teams build and ship software when AI is part of every step?
You will be the technical authority for AI-augmented delivery. Not a theoretical or advisory role – you will define the approach, prove it with real teams and code, and scale it across the engineering organization.
If you enjoy being both strategist and builder, and want your work to change how hundreds of engineers work daily, this is it.
You will create the blueprint for how AI is used responsibly in the SDLC. That includes defining how teams should approach design and spec creation, development, peer review, testing and release when assisted by AI. Your work will include practical standards, reference patterns, and clear controls that keep AI-generated outputs safe, explainable, maintainable and compliant.
You will also continuously assess the market – from coding agents to testing and delivery platforms – and recommend what to adopt, what to avoid, and why.
You will own and evolve the self-serve capabilities that improve engineering throughput and quality. This spans CI/CD guardrails, automated testing, test data solutions, and actionable delivery intelligence (DORA, flow, quality signals).
You will define what good testing looks like in this environment – from unit to contract to E2E to non-functional – and build the evaluation harnesses needed to validate AI-generated artefacts. The goal: less manual toil, faster feedback, more reliable releases.
This is not a slides-only leadership role. You will be in architecture discussions, writing code, building prototypes, reviewing critical paths, and fixing delivery bottlenecks across distributed, cloud-native, API-driven systems. You will run pilots with live product squads, show measurable improvement, and then help scale it.
You will work horizontally across Product, Enterprise Architecture, Security, DevSecOps and the central AI team. A big part of the role is bringing people with you – influencing senior stakeholders, mentoring tech leads and quality engineers, and creating practical forums, guilds and enablement paths that make modern quality engineering stick.