About the position
ABOUT THE ROLE
We are seeking Principal Agentic Software Engineers to join a major digital banking transformation programme and advance enterprise software delivery through AI-assisted engineering.
You will direct AI development agents, review outputs, make architecture decisions and refine the instructions that guide future work. As the senior human-in-the-loop, you will ensure solutions are secure, scalable, maintainable, performant and production-ready.
Success requires strong engineering fundamentals, systems thinking and the ability to adapt to evolving technologies and frameworks.
WHAT YOU'LL DO
AI-Accelerated Engineering
- Deliver enterprise-grade software using AI-assisted and agentic engineering practices.
- Use enterprise AI platforms and tools such as GitHub Copilot and Claude.
- Direct agents using user stories, Figma designs, business rules, design-system components and engineering standards.
- Improve AI Skills, Markdown instruction files, prompts and workflows to enhance quality and delivery speed.
- Build reusable AI-enabled capabilities and critically assess generated outputs.
Full Stack, End-to-End Delivery
- Design, build and maintain frontend and mobile applications, backend services, APIs, integrations, cloud-native components and persistence layers.
- Work across frontend, backend and platform technologies as required.
- Adapt to evolving frameworks, including .NET MAUI, React Native, Flutter and Ionic.
Architecture Engineering Leadership
- Validate architecture and implementation decisions made or proposed by AI agents.
- Ensure solutions are secure, scalable, maintainable, observable and performant.
- Review AI-generated code rigorously and identify architectural drift, technical debt and quality risks.
- Coach engineers in Agentic Engineering practices and uphold technical standards.
Quality Engineering Human-in-the-Loop Assurance
Own the quality of AI-generated solutions, including security, performance, reliability, maintainability, accessibility, observability, automated testing, scalability, CI/CD and DevSecOps.
Continuous Improvement of the Agentic Engineering System
- Use code reviews and delivery feedback to improve AI Skills and instruction files.
- Convert engineering standards, coding conventions and security requirements into reusable agent guidance.
- Assess AI effectiveness, identify where human intervention is needed and improve workflows.
- Help establish the governance and engineering practices required to scale Agentic Engineering.
What Success Looks Like
- Deliver significantly more business value through AI-enabled engineering than traditional development approaches without compromising enterprise quality.
- Rapidly learn and become productive in new frameworks, languages and platforms.
- Improve the quality and effectiveness of the AI engineering ecosystem over time.
- Demonstrate exceptional engineering judgement when validating AI-generated designs and code.
- Consistently deliver secure, scalable, maintainable and production-ready software.
- Raise the technical capability and Agentic Engineering maturity of the teams around you.
Required Experience
Software Engineering
- Typically 8+ years of professional software engineering experience, with demonstrable Principal-level engineering capability.
- Proven experience designing and delivering complex, enterprise-grade software products.
- Strong full stack engineering capability across frontend, backend, APIs, cloud services and data.
- Strong understanding of distributed systems, API-driven architectures and modern application architecture.
- Evidence of operating effectively in complex environments with ambiguity and rapidly changing technology choices.
- Ability to reason from engineering principles rather than relying exclusively on framework-specific knowledge.
Mobile Cross-Platform Engineering
- Strong commercial experience with modern cross-platform mobile engineering.
- Experience with React Native and/or Flutter is strongly preferred.
- Experience with .NET MAUI, Swift, Kotlin or Ionic is advantageous.
- Demonstrated ability to learn unfamiliar frameworks quickly and make sound architecture decisions within them.
AI Agentic Engineering
- Hands-on experience using AI-assisted software development tools such as GitHub Copilot, Claude or equivalent enterprise platforms.
- Experience directing AI agents to perform meaningful software engineering tasks across the delivery lifecycle.
- Experience creating or refining AI Skills, prompt libraries, markdown instruction files, coding agents or reusable engineering workflows.
- Strong understanding of how context, instructions, examples, constraints and feedback loops influence agent quality.
- Ability to recognise AI failure modes including incorrect assumptions, insecure implementations, architectural inconsistency and superficially plausible code.
Technical Excellence
You should be fluent enough in the following disciplines to guide and challenge AI agents effectively:
Software architecture
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Secure software development
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SOLID principles
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Performance engineering
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Design patterns
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Automated testing / TDD
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Domain-driven design
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CI/CD
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API design
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DevSecOps
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Distributed systems
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Observability
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Cloud-native engineering
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Accessibility
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Code quality
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Technical debt management
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The Mindset We're Looking For
AI-Native
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Uses AI as a force multiplier, while retaining accountability for engineering outcomes.
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Framework Agnostic
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Can move between technologies and become productive quickly as the ecosystem changes.
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Systems Thinker
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Understands complete systems, trade-offs and dependencies rather than focusing only on isolated features.
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Engineering Craftsperson
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Treats security, quality, maintainability, testing and performance as non-negotiable.
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Constructively Sceptical
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Challenges agent output, validates assumptions and knows when generated code is not good enough.
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Continuous Learner
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Actively experiments, learns and improves the way software is engineered.
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Multiplier
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Turns personal expertise into reusable Skills, instructions and patterns that improve the performance of the wider engineering system.
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Comfortable with Ambiguity
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Thrives where the right framework, pattern or tool may change during the programme.
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Nice to Have
- Banking or broader financial services experience.
- Experience working with enterprise design systems and reusable UI component libraries.
- Experience translating Figma designs and product requirements into production software.
- Experience in product-led, agile or large-scale digital transformation programmes.
- Experience mentoring senior engineers and influencing architecture across multiple teams.
- Experience establishing engineering standards, governance and reusable developer enablement capabilities.
Desired Skills:
- Systems Analysis
- Complex Problem Solving
- Programming/configuration
- Critical Thinking
- Time Management
