Java Backend Engineer – AI

Build scalable backend applications and integrate AI-powered workflows into complex financial services environments.

At Capco were looking for a Java Backend Engineer with practical experience building AI-powered applications workflows and automation solutions within complex financial services environments.

This role combines strong Java backend engineering with hands-on AI development. Youll build scalable backend services integrate Large Language Models (LLMs) and AI capabilities into enterprise applications and develop intelligent workflows that solve business problems and improve operational efficiency.

Youll also use modern AI-assisted development tools to enhance engineering productivity while maintaining responsibility for code quality security and reliability. Working closely with business stakeholders architects and technology teams youll help turn evolving requirements into practical secure and maintainable solutions.

• Design develop test and maintain scalable backend applications and microservices using Java and Spring Boot.
• Build AI-powered applications workflows and automation solutions using LLMs AI APIs and capabilities such as structured outputs and tool calling.
• Develop REST APIs and integrate AI capabilities with enterprise applications data sources and business processes.
• Use AI-assisted development tools such as GitHub Copilot Cursor Devin or equivalent platforms to accelerate coding testing debugging and delivery while maintaining engineering standards.
• Own technical deliverables from design through implementation testing deployment and production support collaborating with business and technology stakeholders to resolve complex problems.

• 46 years of hands-on software development experience with strong proficiency in Java and backend application development.
• Solid experience with Spring Boot REST APIs microservices system integrations and modern software engineering practices.
• Practical experience building AI-enabled applications or workflows using LLM APIs prompt engineering structured outputs or tool/function calling beyond using AI coding assistants alone.
• Experience using AI-assisted development tools such as GitHub Copilot Cursor Devin or equivalent with the ability to review validate test and securely maintain AI-generated code.
• Experience with automated testing CI/CD version control troubleshooting and end-to-end delivery with an understanding of AI evaluation output validation guardrails privacy and security considerations.

• Experience with Python for AI development automation or supporting backend services.
• Familiarity with retrieval-augmented generation (RAG) embeddings vector databases or hybrid search.
• Exposure to Java AI frameworks such as Spring AI or LangChain4j or frameworks such as LangChain or Semantic Kernel.
• Experience with AI agents workflow orchestration Model Context Protocol (MCP) or human-in-the-loop approval workflows.
• Experience with AWS Azure or GCP Docker Kubernetes or financial services environments such as banking payments capital markets or lending.