1. Role Purpose
The Software Developer (AI) is responsible for designing, developing and maintaining software solutions that support the continued evolution of the Lima platform.
This role combines full-stack software development with practical experience in AI-assisted software engineering, helping to identify opportunities where AI can improve software quality, developer productivity and innovation. The Software Developer supports the adoption of AI-assisted development practices across the team, promoting knowledge sharing and encouraging the effective, secure and responsible use of AI technologies throughout the software development lifecycle.
Working closely with the Head of Lima Development (technical leadership and delivery), the Product Manager (product strategy and roadmap) and the wider development team, this role contributes to the delivery of secure, scalable and maintainable software while supporting continuous improvement and helping build AI capability across the engineering function.
2. Key Responsibilities & Personal Development
Software Development
- Design, develop and maintain features for the Lima platform.
- Deliver high-quality, secure and maintainable software using the Microsoft technology stack.
- Develop, integrate and support secure APIs that enable reliable data exchange between Lima, internal systems and approved third-party services.
- Develop supporting applications, services and tools that enhance the Lima platform and internal business operations.
- Resolve software defects and technical issues in line with agreed quality standards.
- Contribute to technical design discussions and solution implementation.
AI-Assisted Development
- Identify opportunities to use AI-assisted development tools to improve software quality, developer productivity and delivery efficiency.
- Apply AI technologies throughout the software development lifecycle, including design, coding, testing, debugging and documentation.
- Evaluate AI-generated code to ensure it meets quality, security and maintainability standards before implementation.
- Explore emerging AI development capabilities and recommend practical improvements to development processes.
Knowledge Sharing & Continuous Improvement
- Promote the effective and responsible use of AI-assisted development practices across the development team.
- Share knowledge, practical techniques and lessons learned to help develop AI capability within the engineering function.
- Contribute to the development of coding standards, reusable components and development best practices.
- Support colleagues with technical guidance and peer code reviews where appropriate.
Collaboration
- Work closely with the Product Manager to understand product requirements and translate these into technical solutions.
- Collaborate with the Head of Lima Development to ensure solutions align with the overall technical architecture and delivery approach.
- Work with the wider development team to deliver software that meets customer and business requirements.
- Support troubleshooting and customer issues relating to the Lima platform where required.
API Development & Integration
- Design, build and maintain RESTful APIs and service integrations that support scalable, secure and maintainable platform functionality.
- Apply appropriate API authentication, authorisation, validation, error handling and logging controls in line with secure development standards.
- Produce and maintain clear API documentation to support development, testing, integration and ongoing support activities.
- Work with colleagues and stakeholders to understand integration requirements and ensure APIs meet business, product and operational needs.
Quality & Delivery
- Ensure software meets agreed coding, security and quality standards.
- Participate in testing, code reviews and release activities.
- Contribute to continuous improvement of development processes and engineering practices.
- Maintain appropriate technical documentation to support ongoing development and support activities.
Personal Development
- Maintain knowledge of current software development frameworks, languages and engineering practices.
- Continue developing expertise in AI-assisted software development and emerging technologies.
- Share learning and best practice with the wider development team.
- Identify opportunities to improve engineering capability through innovation and continuous improvement.
3. Knowledge/Experience/Technical Skills/Behaviours
a) Knowledge/Experience/Technical Skills
Essential: -
- Proven experience across the full software development lifecycle.
- Strong knowledge of C#, .NET, ASP.NET, SQL Server, HTML, CSS and JavaScript.
- Experience developing enterprise software applications using Microsoft technologies.
- Experience developing, consuming and supporting APIs, including RESTful services and secure system integrations.
- Understanding of API authentication, authorisation, validation, error handling, logging and documentation principles.
- Experience with Visual Studio and Microsoft SQL Server.
- Good understanding of Agile software development methodologies.
- Demonstrable experience using AI-assisted software development tools within commercial software engineering.
- Experience applying AI to software design, coding, debugging, testing and documentation.
- Ability to critically review and validate AI-generated code for quality, security and maintainability.
- Understanding of secure software development principles.
- Strong problem-solving and analytical skills.
- Ability to communicate technical concepts effectively.
- Experience working collaboratively within a software development team.
Desirable: -
- Experience with GitHub Copilot, Microsoft Copilot, ChatGPT Enterprise or equivalent AI-assisted development tools.
- Experience integrating AI or Large Language Models (LLMs) into software applications.
- Experience designing APIs using OpenAPI/Swagger or similar documentation standards.
- Experience with Azure DevOps and CI/CD pipelines.
- Experience with Windows Presentation Foundation (WPF).
- Experience with DevExpress.
- Experience with Test Driven Development (TDD).
- Knowledge of Azure AI Services or Microsoft AI technologies.
- Experience working within digital forensics, investigations or case management environments.
b) Behaviours
- Delivers high-quality software with attention to detail.
- Curious about emerging technologies and actively explores opportunities to improve software engineering practices.
- Promotes the responsible and effective use of AI within software development.
- Shares knowledge openly and supports the development of colleagues.
- Collaborative and works effectively across technical and non-technical teams.
- Takes ownership of work and delivers to agreed timescales.
- Customer-focused and committed to delivering value.
- Demonstrates integrity and professionalism.
- Approachable and supportive.
- Continuously seeks opportunities to improve products, processes and ways of working.
4. Key Success Measures
- Delivery of high-quality software aligned with product and business objectives.
- Successful implementation of new features within agreed timescales.
- Delivery and support of secure, well-documented APIs that enable reliable internal and external system integration.
- Contribution to software quality through reduced defects and improved maintainability.
- Increased adoption of AI-assisted development practices across the engineering team.
- Positive contribution to developer productivity through the effective use of AI technologies.
- Knowledge sharing and support that improves AI capability within the wider development team.
- Positive contribution to continuous improvement of engineering standards and development processes.