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Design and build large-scale internet/intranet web application platforms on microservices architecture, owning decisions across the full stack — from Angular frontends to Java/Spring Boot backends and MongoDB data layer
Lead system design at both high and low levels, producing artefacts such as sequence diagrams, class diagrams, and data models, while ensuring security, scalability, and performance are built in from the start
Leverage AI coding agents (e.g., Claude Code, Cursor, Devin) for code generation, debugging, and routine tasks
engineering high-quality context (repository structure, API specs, Jira tickets) to maximize the accuracy and reliability of AI output
Critically review, validate, and take ownership of all AI-generated code ensuring structural integrity, security compliance, and production readiness before anything reaches deployment
Integrate agentic workflows into CI/CD pipelines
manage multiple workstreams concurrently through intelligent delegation to AI agents
Act as a player/coach within small, co-located squads — hands-on in delivery while actively upskilling junior engineers to become effective AI-first practitioners
Apply a strong functional understanding of Corporate Banking to ensure solutions address real business outcomes, not just technical requirements
Requirements
6+ years' hands-on experience with Java and Spring Boot for building scalable microservices, and Angular 16+, TypeScript, JavaScript, HTML5, JSON, CSS, Web Sockets, and Ajax
Proven experience designing large-scale internet/intranet platforms using microservices architecture
Strong fundamentals in systems analysis, design patterns, and SDLC, including unit testing and CI/CD practices
Ability to produce high-level and low-level design artefacts (sequence diagrams, class diagrams)
Proficiency in Python for scripting, automation, or AI-adjacent tooling
Hands-on experience with MongoDB
solid understanding of modern database design and data modelling
Good understanding of message brokers
Kafka experience highly desirable
Demonstrated, hands-on proficiency with AI coding tools (e.g., Claude Code, Cursor, GitHub Copilot, or equivalent)
Spec driven development - Ability to write structured prompts, engineer context, and decompose complex problems into tasks suitable for AI agent delegation
Proven ability to identify and resolve AI failure modes before they reach production
Strong experience with GitHub for source control and Jira for project management
Proven experience in Agile/Scrum delivery
Functional understanding of Corporate Banking — able to articulate why their work matters, not just how it is built
Bachelor’s degree/University degree in Engineering, Finance, or equivalent experience