全职 Principal Engineer (AI-Driven Software Delivery) 工作, 薪水, SP Group 公司招聘中 - Ricebowl

About SP Group

SP Group is a leading utilities group in the Asia Pacific, operating Singapore’s electricity and gas transmission and distribution networks. We are committed to delivering reliable and sustainable energy solutions and driving innovation through digital and AI-enabled initiatives across our business domains.

About the Role

We are seeking an experienced Principal Engineer, AI-Driven Software Delivery to help shape how SP Digital Engineering builds, tests and delivers software in the AI era. This is a hands-on technical leadership role focused on improving developer productivity, software quality and delivery confidence through AI-assisted engineering practices, modern delivery platforms and automated quality controls.

The successful candidate will work across engineering, architecture, DevSecOps, cyber security, product and business teams to establish practical standards, reusable patterns and self-service capabilities that accelerate software delivery while maintaining reliability, security and compliance. The role is well suited for a senior engineering leader or architect from a technology, consulting, systems integration or enterprise engineering background who enjoys combining hands-on engineering with organisation-wide influence.

What You'll Do:

AI-Driven Software Delivery Strategy & Technical Leadership

• Define and drive the strategy, roadmap and engineering standards for AI-driven software delivery across SP Digital Engineering.
• Establish consistent practices for requirements specification, solution design, coding, code review, testing, release and production readiness in an AI-assisted engineering environment.
• Design practical guardrails to ensure AI-assisted delivery remains secure, traceable, maintainable and subject to appropriate engineering review.
• Develop reusable playbooks, reference architectures, templates and automation patterns that enable teams to adopt AI-driven delivery practices consistently.
• Evaluate emerging AI engineering tools, coding agents and delivery technologies, and recommend adoption based on measurable value, security, cost and operational suitability.

Developer Productivity & Quality Engineering Platforms

• Lead the design and adoption of developer productivity and quality engineering capabilities, including automated testing, test data, CI/CD quality gates and software delivery metrics.
• Define enterprise-ready test automation patterns across unit, API, contract, integration, end-to-end, performance, resilience and security testing.
• Establish repeatable evaluation, regression testing and quality verification approaches for AI-generated code, specifications, tests and documentation.
• Improve software delivery flow by reducing manual effort, improving test reliability, shortening feedback cycles and increasing confidence in releases.
• Use engineering metrics and quality insights to identify delivery bottlenecks, systemic risks and opportunities for continuous improvement.

Hands-on Engineering & Delivery

• Provide hands-on technical leadership through architecture reviews, prototyping, coding, test design, code review, tooling implementation and troubleshooting.
• Lead the resolution of complex delivery challenges involving distributed systems, APIs, cloud platforms, engineering toolchains and release pipelines.
• Partner with product and engineering teams to pilot new practices, demonstrate measurable impact and support adoption across live delivery teams.
• Ensure solutions comply with SP Group engineering, security, architecture, risk and regulatory requirements.

Stakeholder Engagement & Capability Development

• Lead cross-functional initiatives involving Engineering, Product, Architecture, DevSecOps, Cyber Security, AI CoE and business stakeholders.
• Communicate technical recommendations, risks and trade-offs clearly to engineering leaders and governance forums.
• Mentor and coach senior engineers, technical leads and quality engineers in AI-assisted development and test automation.
• Develop practical playbooks, workshops and communities of practice to strengthen engineering capability and promote consistent adoption.

What You'll Need:

Experience

• Minimum 10 years of progressive experience in software engineering, platform engineering, quality engineering or technology delivery, including technical leadership across multiple teams.
• Proven experience defining and implementing engineering practices, delivery standards, reusable platforms or cross-team technical capabilities in large-scale environments.
• Demonstrated experience improving software delivery outcomes through automation, quality engineering, DevOps, developer experience or enterprise engineering transformation initiatives.
• Practical experience using AI-assisted engineering tools, coding assistants, large language models or intelligent automation within governed delivery environments.
• Experience working in or with enterprise technology organisations, consulting firms, systems integrators or high-assurance digital platforms is advantageous.

Technical Skills

• Strong proficiency in at least one major programming language such as Java, C#, Python,
• JavaScript/TypeScript or Go, with the ability to review and guide engineering implementation.
• Deep knowledge of modern software delivery practices, including CI/CD, automated testing, observability, release quality, engineering metrics and delivery assurance.
• Strong understanding of software architecture, distributed systems, API design, cloud platforms, container technologies and enterprise integration patterns.
• Experience with delivery toolchains such as GitHub, GitHub Actions, Jenkins, Azure DevOps, SonarQube, test automation frameworks or similar platforms.
• Good understanding of secure SDLC, DevSecOps, software supply-chain risks and relevant standards such as OWASP, NIST SSDF or ISO/IEC 27001.

Desired Skills & Attributes

• Hands-on and outcome-oriented, with the ability to translate engineering strategy into practical delivery capabilities adopted by teams.
• Strong analytical, problem-solving and decision-making skills.
• Excellent communication and stakeholder management skills, with the ability to influence senior engineers, delivery leaders, architects and governance forums.
• Ability to operate across teams, manage ambiguity and drive adoption of new engineering practices in complex enterprise environments.
• Strong coaching mindset and commitment to continuous learning and knowledge sharing.
• Experience in utilities, critical infrastructure, regulated digital services or other high-assurance environments is advantageous.

What We'll Provide:

• Opportunity to shape AI-driven software delivery practices across a mission-critical digital engineering organisation.
• Work on digital platforms that support Singapore’s energy ecosystem, customer services and regulated digital operations.
• Collaborate with multidisciplinary teams across engineering, architecture, cyber security, DevSecOps, data, AI and business domains.
• Lead meaningful engineering transformation work with visibility across senior technology and business stakeholders.
• Competitive remuneration and benefits.