Job Description

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.

The Mandate
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.

Key Responsibilities

A. Set the Model for AI in Engineering
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.

B. Build the Platforms That Make Teams Faster and Safer
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.

C. Stay Hands-On
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.

D. Scale Capability and Influence
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.

Who This Suits

A senior engineer / architect with 10+ years shipping complex software at scale, with experience leading across multiple teams or domains.
Someone who has successfully introduced new ways of working, platform capabilities or engineering standards in a large, complex organisation.
Proven impact in one or more of: DevOps, developer experience, test automation, or engineering productivity.
Real, practical exposure to using GenAI / LLMs / coding assistants in delivery - beyond experimentation, with an understanding of enterprise governance.
Comfortable coding and guiding others in one or more of: Java, C#, Python, TypeScript/JavaScript, Go.
Strong fundamentals in cloud, containers, distributed systems, APIs, CI/CD, observability and modern quality engineering.
Toolchain fluency - e.g. GitHub ecosystem, Jenkins / Azure DevOps, SonarQube, and leading test automation stacks.
Profile: builder mindset, data-driven, clear communicator, able to navigate ambiguity and drive adoption in a matrixed environment.