Technical Lead (Java & AI)

We are working with a fast-growing Insurance Services client, who is looking for a hands-on Technical Lead to drive the design, delivery and evolution of a modern, AI-enabled engineering platform. This role offers the opportunity to combine technical leadership with hands-on development, leading a talented team whilst shaping architecture, engineering standards and the adoption of AI-driven capabilities across the organisation.

Responsibilities

Lead the architecture, design and delivery of scalable cloud-native applications and services; Define service boundaries, integration patterns, data models and non-functional requirements; Drive engineering best practices across code quality, security, performance and testing; Remain actively involved in software development, solving complex technical challenges; Lead and mentor a team of engineers through coaching, reviews and technical guidance; Own sprint planning, estimation, delivery forecasting and release quality; Collaborate with Product, Architecture, QA and DevOps teams to align technical and business objectives; Drive observability, monitoring, resilience and incident management standards; Support recruitment, technical assessments and onboarding activities; Lead the design and implementation of AI-enabled product capabilities; Architect and deliver RAG, semantic search and vector database solutions; Champion effective use of AI-assisted development tools across engineering teams; Evaluate emerging technologies and provide strategic technical recommendations

Requirements

8–12 years' experience in software engineering with deep Java expertise; Previous experience leading engineering teams or owning technical delivery outcomes; Expert-level knowledge of Java 17+ and modern Spring Boot ecosystems; Strong understanding of microservices, distributed systems and scalable architecture design; Experience with workflow automation or BPM platforms; Advanced SQL and database design expertise; Strong knowledge of API security, authentication and secure software development practices; Experience owning CI/CD pipelines and deployment automation strategies; Demonstrable experience delivering AI-enabled solutions in production or near-production environments; Knowledge of LLM integrations, vector databases, prompt engineering and RAG architectures; Experience guiding engineering teams in the adoption of AI tools and practices; Strong Agile delivery and stakeholder management experience; Excellent leadership, communication and mentoring skills; Passion for balancing technical excellence with successful business delivery