Java Tech Lead Hybrid, 4 days on site per month in Telford Inside IR35, £550/£600 6 months scope to extend Role Overview Provide technical leadership for the design, development and delivery of Java-based RESTful APIs and microservices as part of an application modernisation programme. Lead engineering standards, technical design and solution implementation, ensuring scalability, resilience, maintainability and integration with existing systems. Essential Skills Java - Extensive hands-on backend development experience, with the ability to provide technical guidance and undertake complex development. Spring Boot - Strong expertise in RESTful API and microservices development. Microservices Architecture & Design - Designing scalable, resilient and loosely coupled services, including service-to-service communication and integration patterns. API Architecture & Design - API contracts, versioning, security, integration patterns and performance optimisation. Application Modernisation - Experience modernising legacy applications, service decomposition and integration with existing systems. Docker & Kubernetes - Containerisation, deployment and management of microservices. Technical Leadership - Leading developers, providing technical direction, mentoring and resolving complex engineering challenges. Engineering Standards - Establishing development standards, conducting code reviews and ensuring code quality, security and maintainability. Testing & Quality - JUnit, automated testing practices and test-driven development. Git / CI/CD - Version control, build automation and deployment pipelines. Technical Design & Delivery - Translating architectural requirements into technical designs, managing technical dependencies and supporting delivery planning.Desirable Skills AWS JPA / Hibernate Maven / Gradle Mockito GitLab Helm OpenAPI / Swagger SQL Kibana Observability and performance monitoring Event-driven architecture / messaging Shell scriptingAI-Assisted Development & Leadership Willingness to actively embrace and promote the effective use of approved AI tools and agents throughout the software development lifecycle, including technical analysis, solution design, code generation, testing, code reviews and continuous improvement. Ability to guide engineering teams in adopting AI-assisted development practices while maintaining security, quality and governance standards