Principal Agentic Software Engineer
Summary
A senior (Principal) engineer on a digital banking transformation programme who directs and reviews AI coding agents (GitHub Copilot, Claude), makes architecture decisions, and builds reusable AI guidance. Day to day: full-stack and cross-platform mobile delivery (React Native/Flutter/.NET MAUI), validating AI-generated designs and code for security, scalability and quality.
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.
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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.
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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.
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Technical Excellence
You should be fluent enough in the following disciplines to guide and challenge AI agents effectively:
Software architecture | Secure software development |
SOLID principles | Performance engineering |
Design patterns | Automated testing / TDD |
Domain-driven design | CI/CD |
API design | DevSecOps |
Distributed systems | Observability |
Cloud-native engineering | Accessibility |
Code quality | Technical debt management |
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The Mindset We're Looking For
AI-Native | Uses AI as a force multiplier, while retaining accountability for engineering outcomes. |
Framework Agnostic | Can move between technologies and become productive quickly as the ecosystem changes. |
Systems Thinker | Understands complete systems, trade-offs and dependencies rather than focusing only on isolated features. |
Engineering Craftsperson | Treats security, quality, maintainability, testing and performance as non-negotiable. |
Constructively Sceptical | Challenges agent output, validates assumptions and knows when generated code is not good enough. |
Continuous Learner | Actively experiments, learns and improves the way software is engineered. |
Multiplier | Turns personal expertise into reusable Skills, instructions and patterns that improve the performance of the wider engineering system. |
Comfortable with Ambiguity | 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.