Technical lead

Technical Lead – Java (AI Enabled)

Engineering · UK

About Xceedance

Xceedance is a global provider of strategic consulting, managed services, and technology solutions to the insurance industry. We help insurers, reinsurers, brokers, and MGAs modernize operations, enhance underwriting and claims capabilities, and accelerate digital transformation using data, analytics, and advanced platforms.

We are seeking an accomplished Technical Lead with deep Java expertise and demonstrated experience integrating AI/ML capabilities into production systems. This role combines hands-on engineering with technical leadership — you will own the architecture and delivery of cloud-native microservices on our BPA (Beyond Policy Administration) platform, lead a team of engineers, and drive the adoption of AI tooling and AI-driven product features across the engineering organisation.

The right candidate still loves to code, thinks in systems and trade-offs, raises the technical bar of everyone around them, and has already shipped or championed AI-enabled capabilities — not just experimented from the sidelines.

Role Details

Location: London

Experience: 8–12 years of overall software engineering experience, including 2+ years leading engineering teams or owning technical delivery

Engagement Model: Full-time, Product Engineering

Job Responsibilities

• Own the high-level and low-level design of services on the BPA platform — define service boundaries, integration contracts, data models, and non-functional requirements.
• Lead architecture and design reviews; set and enforce engineering standards for code quality, security, performance, and testability across the team.
• Design and implement RESTful APIs and microservices using Java 17+ and Spring Boot 3.x — this is a hands-on role; expect to spend meaningful time in the codebase on the hardest problems.
• Drive resilience and scalability patterns (Circuit Breaker, Retry, Bulkhead, backpressure) and own production architecture decisions for your domain.
• Identify, prioritise, and systematically retire technical debt; balance delivery speed against long-term platform health.
• Lead, mentor, and grow a team of 4–8 engineers — through design walkthroughs, pair programming, rigorous code reviews, and structured feedback.
• Own sprint delivery for your team: break epics into stories, drive estimation, surface risks and dependencies early, and be accountable for predictable, high-quality releases.
• Collaborate with Product, QA, DevOps, and Architecture groups to align technical roadmaps with business priorities.
• Run production readiness reviews; own observability standards (structured logging, metrics, distributed tracing, alerting) and incident response maturity for your services.
• Contribute to hiring — interviews, technical assessments, and onboarding of new engineers.
• Lead the design and delivery of LLM-based capabilities (e.g., OpenAI, Gemini, Claude) within Java services — document extraction, policy summarisation, intelligent routing — including evaluation, guardrails, cost, and latency considerations.
• Architect retrieval-augmented generation (RAG) solutions using vector-search platforms (e.g., OpenSearch, Pinecone), owning decisions on chunking, embeddings, retrieval quality, and context management.
• Champion fluent use of AI coding assistants (Claude Code, GitHub Copilot, Cursor, etc.) across the team — set usage standards, measure impact on throughput and quality, and coach engineers on effective adoption.
• Establish patterns for prompt design, context management, response parsing, and testing of AI-enhanced features.
• Stay current with applied AI developments; evaluate emerging tools and frameworks and bring pragmatic recommendations to engineering leadership.

Essential Qualifications and Skills

• 8–12 years of hands-on Java development experience; expert-level command of modern Java (17+) is non-negotiable.
• 2+ years leading engineering teams or operating as a tech lead / lead engineer with ownership of design and delivery outcomes.
• Deep Spring Boot expertise: REST APIs, Spring Security, Spring Data, Spring Cache; proven ability to set patterns others follow.
• Strong command of microservices architecture and distributed-systems fundamentals — resilience patterns, consistency trade-offs, API versioning, and inter-service communication.
• Experience with Camunda BPM or similar workflow engines, including designing workflow-driven business processes.
• Strong SQL and PostgreSQL skills, including schema design and query optimisation; depth in ORM frameworks (Hibernate/JPA).
• Practical Git leadership: branching strategy ownership (trunk-based development or GitFlow), code review culture, and release management.
• Working knowledge of OAuth2 / OpenID Connect, JWT, secure API design, and threat-modelling basics.
• Experience owning CI/CD pipelines (Azure DevOps, GitHub Actions, or equivalent) and driving deployment automation and quality gates.
• Demonstrated production (or near-production) experience with at least one of: LLM API integration, vector databases, prompt engineering, or RAG pipeline construction.
• Familiarity with REST-based AI APIs (OpenAI, Anthropic, Google Vertex AI, or equivalent) and a working understanding of embeddings, semantic search, and token-based context management.
• Comfortable reading Python code or notebooks (most AI libraries are Python-first); ability to translate patterns into robust Java implementations and guide others in doing so.
• Active, fluent use of AI coding tools in your current workflow — and a point of view on where they help and where they don’t.
• Strong Agile delivery experience — sprint planning, story decomposition, backlog grooming, retrospectives — including facilitating these ceremonies for a team.
• Strong testing leadership: unit, component, and integration testing discipline (JUnit 5, Mockito, Testcontainers); exposure to BDD or contract testing is a plus.
• Deep appreciation for observability: structured logging, distributed tracing, metrics, and alerting hygiene.

Desirable Qualifications and Skills

• Insurance or Insurtech domain knowledge — Policy Administration, Claims, or Underwriting workflows.
• Familiarity with Kafka or event-streaming patterns (producing, consuming, DLQs, retries) at design-ownership level.
• Knowledge of containerisation and orchestration: Docker, Kubernetes/AKS, including capacity and cost considerations.
• Exposure to LangChain4j, Spring AI, or similar Java-native AI integration frameworks.
• Understanding of ACORD data standards.
• Experience presenting technical decisions to senior stakeholders or contributing to architecture governance forums.

What Good Looks Like

The strongest candidates will show us — not just tell us — both their leadership and their AI engagement. That might be a service or platform you architected and the trade-offs you navigated, a team you grew and the engineers you developed, a RAG pipeline or LLM integration you took to production, or how you led your team’s adoption of AI coding tools and what measurably changed. We are not hiring a people manager who has stopped coding, nor a pure individual contributor; we are hiring a hands-on technical leader who raises the bar on engineering quality and is already applying AI rather than watching it from the sideline.

Our Promise to You

At Xceedance, we foster an inclusive, supportive, fun yet challenging team environment. We value a team composed of diverse backgrounds and respect the healthy expression of diverse opinions.

You will be joining a team of experts reshaping the global insurance landscape. We champion innovation, foster professional growth, and make a meaningful impact through cutting-edge technology. We are an equal opportunity employer.