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# Java Developer (SC Eligible/ Cleared)

- **Company:** Inclusionat Scrumconnect Consulting
- **Location:** London, UK
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Clean Code Principles, Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Audit Trail, Microsoft Azure, Cloud Computing, Code Review, Databases, Continuous Integration, Decision Support Systems, DevOps, Github, Gradle, Junit, Apache Maven, NoSQL, Scrum Methodology, RabbitMQ, Mockito, Data Streaming, Systems Architecture, Systems Integration, Data Logging, Test-Driven Development (TDD), Large Language Models, Multi-Agent Systems, Prompt Engineering, Spring-boot, Backend, Git, Kotlin, Event Driven Architecture, Gitlab-ci, Information Technology, Apache Kafka, Graphql, Api Design, Cucumber (Software), Jenkins, Web Api
- **Published:** September 21, 2026
- **Apply:** https://www.apply4u.co.uk/jobs/java-developer-sc-eligible-cleared/47842314

## About the Role

with QA, DevOps, and product teams within an Agile/Scrum delivery model. Technical Skills Core Backend Languages: Java 11/17/21 (or later), with working knowledge of Kotlin/Scala a plus Messaging/Streaming: Kafka, RabbitMQ, event-driven architecture Testing: JUnit, Mockito, TDD/BDD, Cucumber Build & CI/CD: Maven/Gradle, Git, Jenkins/GitHub Actions/GitLab CI Understanding of LLM agent architectures : reasoning loops, tool-use, planning, and memory patterns. Hands-on experience (or strong aptitude to learn) building or integrating agents using frameworks such as LangChain, LangGraph, AutoGen, CrewAI , or the Model Context Protocol (MCP) . Ability to design and expose backend services as tools/functions callable by AI agents (tool schemas, function calling, structured outputs). Experience with retrieval-augmented generation (RAG) : vector databases (e.g., Pinecone, Weaviate, pgvector), embeddings, and chunking strategies. Working knowledge of prompt engineering and evaluation techniques
for agent reliability, safety, and cost control. Familiarity with orchestrating multi-agent workflows and human-in-the-loop approval steps for sensitive actions. Awareness of security, data-privacy, and governance considerations specific to AI agents (prompt injection risks, access scoping, audit logging). Experience integrating with LLM provider APIs (e.g., Anthropic Claude API, OpenAI API) including streaming responses and tool-result handling. Qualifications & Experience Bachelor's degree in Computer Science or related field, or equivalent demonstrable experience. 10-15 years' commercial backend development experience. Proven experience delivering production-grade services in Agile/Scrum teams. Exposure to (or strong interest in) integrating AI/LLM capabilities into production systems. Good communication skills; comfortable explaining technical trade-offs to both technical and non-technical stakeholders. Diversity & InclusionAt Scrumconnect Consulting, we believe that diversity drives
innovation. We are committed to creating an inclusive environment where every individual is respected, valued, and supported.We welcome applications from candidates of all backgrounds and experiences, and we actively encourage applications from women, people with disabilities, under-represented communities, and those seeking flexible working arrangements. #J-18808-Ljbffr

## Description

and maintain backend services and REST/GraphQL APIs using Java/Spring Boot (or equivalent modern backend stack). Contribute to system architecture and data model design in collaboration with senior/lead engineers. Write clean, well-tested, maintainable code following TDD/BDD practices and team coding standards. Participate in code reviews, providing and receiving constructive feedback. Integrate backend services with databases (relational and NoSQL), messaging/event systems, and third-party APIs. Build, extend, and operate agentic AI workflows - integrating LLM-based agents and tools into backend systems for automation, orchestration, and decision support. Support CI/CD pipelines, containerised deployments, and cloud infrastructure (AWS/Azure) for services owned by the team. Diagnose and resolve production issues, contributing to monitoring, logging, and observability practices. Document technical designs, APIs, and agent workflows clearly for other engineers and stakeholders. Work closely


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