Principal Engineer (Engineering Practice)

The Opportunity

The Principal Engineer in Asia & Middle East Tech (AMET) is a senior technical leader who uplifts engineering capability, efficiency and productivity across multiple teams. You’ll set technical direction, accelerate adoption of modern engineering practices and tooling, and drive responsible integration of AI into the development environment and, where appropriate, production systems—balancing innovation with governance, model risk, explainability and data privacy. You’ll work across boundaries with product, security, risk and operations to deliver resilient outcomes in a regulated environment.

Key responsibilities

1) Drive AI adoption at scale

• Define and execute an AI adoption roadmap across the engineering organisation (e.g., coding assistance, test generation, incident support, documentation, knowledge search, SDLC automation).
• Identify high-value use cases, prioritise them with measurable outcomes, and take them from prototype to production.
• Establish repeatable patterns (playbooks, templates, golden paths) so teams can adopt AI consistently.

2) Technical leadership

• Design reference patterns for AI-enabled engineering workflows (e.g., RAG for internal knowledge, secure prompt patterns, evaluation harnesses, model routing, guardrails).
• Lead technical decisions on build vs buy, model selection, integration patterns, and platform capabilities.
• Ensure solutions align with enterprise architecture, cloud strategy, and engineering standards.

3) Responsible AI, security, and risk-by-design

• Embed controls for data handling, privacy, IP protection, and secure SDLC when using AI tools.
• Partner with Cyber Security, Risk, Compliance, and Legal to ensure safe usage patterns and approvals.
• Define governance for prompts, datasets, model outputs, and human-in-the-loop review where required.

4) Engineering excellence & transformation outcomes

• Improve engineering productivity and quality through AI-enabled automation (CI/CD, code review, testing, release, observability).
• Define and track metrics (e.g., lead time, change failure rate, MTTR, test coverage, defect escape rate, developer satisfaction).
• Champion modern engineering practices (platform engineering, DevSecOps, SRE, trunk-based development) and show how AI amplifies them.

5) Enablement, coaching, and community building

• Coach engineers and tech leads on effective AI usage (prompting, evaluation, safe patterns, limitations).
• Run workshops, office hours, and internal communities of practice; create learning paths and onboarding materials.
• Mentor senior engineers and help raise the technical bar across teams.

6) Stakeholder management & influence

• Work closely with Heads of Engineering, Product Owners, Architecture, and Operations to align priorities and remove blockers.
• Communicate clearly to technical and non-technical audiences; influence without authority across multiple teams and regions.
• Provide pragmatic guidance—balancing pace with safety, quality, and long-term maintainability.

Required experience & skills

• Degree in Computer Science/Engineering or related discipline; MSc/PhD preferred.
• 10+ years’ software engineering experience, ideally in financial services or other regulated environments.
• Proven track record improving engineering capability and delivery outcomes through modern engineering practices, standards and developer tooling.
• Practical experience applying AI/ML or GenAI in engineering contexts (e.g., copilots, RAG, code intelligence, test generation, incident triage).
• Experience designing secure, scalable platforms and APIs; familiarity with cloud-native patterns and CI/CD.
• Strong understanding of SDLC, DevSecOps, and production operations (observability, incident management, SRE practices).
• Excellent communication and coaching skills; able to lead through influence.

Preferred / nice-to-have

• Experience building internal developer platforms or “golden paths”.
• Familiarity with model evaluation, prompt engineering patterns, and guardrail techniques.
• Experience with regulated environments (financial services) and working with risk/compliance stakeholders.
• Contributions to internal standards, reusable libraries, open source, research, patents, or speaking at conferences.