Overview
As an Agentic Software Engineer at RGI, you will contribute to the development of the IIAB software ecosystem using a structured, AI-augmented delivery framework.
You will work across the end-to-end lifecycle of a User Story - from functional review and technical analysis through coding, testing, release and system validation. You will use AI coding assistants and specialised agents to improve speed and productivity, while remaining directly accountable for the quality of the final delivery.
This opportunity is particularly suited to an experienced Java/backend engineer who combines strong technical foundations with critical thinking, process discipline and an interest in how AI can improve software engineering. Success in the role is not measured only by the volume of code produced, but by the reliability, coherence, testability and maintainability of the complete solution.
Key Responsibilities
- Use RGI's agentic development framework across functional review, technical analysis, test design, mocks and guardrails, coding, unit testing, release and system testing.
- Interpret functional requirements and User Stories, translating them into robust technical analyses and solutions aligned with the application architecture, product standards and project constraints.
- Develop and maintain enterprise Java/backend components, APIs and application integrations.
- Use GitHub Copilot, Claude, ChatGPT or comparable AI tools to support technical analysis, coding, testing and defect investigation.
- Critically review AI-generated analysis, code, tests and documentation, identifying logical errors, inconsistencies, hallucinations, missing context and deviations from engineering guidelines.
- Own the relevant quality gates and ensure that delivery controls are completed without shortcuts that could compromise reliability or release quality.
- Investigate defects, regressions and anomalies, distinguishing between issues caused by code, configuration, context or the interpretation of functional requirements.
- Collaborate closely with Business Analysts, Technical Leaders, Product Owners, senior developers, R&D colleagues and AI teams.
- Contribute to the continuous improvement of the development process by enriching knowledge bases and standardising effective prompts, queries, examples and reusable engineering patterns.
Professional Experience
- Solid hands-on experience in enterprise Java/backend software development.
- Experience delivering and supporting complex applications, ideally in structured or mission-critical enterprise environments.
- Practical experience turning functional requirements into technical analysis, code and testable solutions.
- Experience working with Agile delivery methods, code-review practices, quality gates and structured release processes.
- Practical use of AI coding assistants in software development, with the ability to explain how their output was verified and improved.
- Insurance-domain experience is a strong advantage, particularly across policy administration, claims, product configuration, billing or system integrations.
Technical Expertise
- Strong knowledge of Java and enterprise backend development.
- Practical experience with Spring, Spring Boot or comparable Java frameworks.
- Experience with REST APIs, web services and application integrations.
- Good knowledge of SQL and relational databases.
- Experience with Git, branching models, collaborative code review and CI/CD pipelines.
- Strong unit-testing, integration-testing and structured debugging skills.
- Ability to construct effective prompts and provide AI tools with clear, relevant technical context.
- Understanding of the limitations of large language models, including hallucination, context loss, incomplete reasoning and overconfidence.
- Familiarity with RAG, knowledge bases, specialised AI agents, MCP or broader agentic workflows is useful but not essential.
Italian language is required for day-to-day collaboration.
Good professional English is required.
What We Value
- Strong technical judgement and a willingness to challenge outputs rather than accept them at face value.
- A hands-on attitude and the curiosity to experiment with new tools, workflows and development practices.
- Structured problem solving and the patience to investigate complex issues in depth.
- Ownership of quality across the complete delivery cycle, not only the coding phase.
- Clear communication and the ability to collaborate effectively with both functional and technical colleagues.
- A disciplined approach to standards, documentation, testing and continuous improvement.
What We Offer
- A role at the intersection of software engineering, artificial intelligence and insurance product development.
- The opportunity to help shape and improve a structured agentic software-development framework in a real enterprise environment.
- Hands-on exposure to complex insurance platforms and mission-critical delivery challenges.
- Close collaboration with Product, Business Analysis, Technical Leadership, R&D and AI specialists.
- Continuous learning and professional growth as AI-augmented engineering practices evolve.
Education
A degree in Computer Science, Computer Engineering or a related discipline is preferred, although equivalent practical experience will also be considered.
