AI Automation & Software Engineer

Why join us? Join a lean, forward-thinking family office where AI and software engineering are transforming how we innovate, operate and make decisions. Working directly with leadership, you'll design and build AI-powered platforms, enterprise applications and intelligent solutions that solve real business challenges. This is a high-ownership role where AI is a strategic investment, giving you the opportunity to build production-ready solutions and help shape our organisation's AI capabilities. If you're passionate about building meaningful software and intelligent systems that make a real impact, we'd love to hear from you. 1. Synopsis of the role: The AI Automation & Software Engineer will design, develop and maintain modern enterprise applications, AI-powered software solutions, intelligent agents and business automation platforms that improve operational efficiency and decision-making across the organisation. The role combines software engineering, AI application development, system integration and intelligent automation to deliver secure, scalable, production-ready solutions while supporting and modernising existing .NET applications. Software engineering within the organisation follows an AI-first approach. Developers are expected to leverage modern AI-assisted development tools and coding assistants throughout the software development lifecycle, while applying sound engineering judgement to deliver secure, scalable and maintainable production systems. 2. Essential functions: Software Engineering- Design, develop and maintain secure, scalable enterprise applications, backend services, APIs and responsive web applications. Support, modernise and extend existing .NET applications. Design reusable software components and scalable architecture that supports maintainability and future AI integration. AI Engineering- Design and develop production-ready AI-powered applications using Large Language Models (LLMs) and AI services. Build AI agents capable of reasoning, workflow orchestration, tool calling and enterprise automation. Develop Retrieval-Augmented Generation (RAG) solutions using enterprise knowledge sources. Integrate AI capabilities into enterprise applications and business workflows. Evaluate emerging AI models, frameworks and AI-assisted development tools, leveraging technologies such as OpenAI Codex, Claude Code, GitHub Copilot or similar throughout the software development lifecycle. Business Automation & Decision Intelligence- Design intelligent automation solutions that streamline operational, financial and business processes. Develop AI-powered workflows, dashboards, reporting platforms and decision-support applications. Design intelligent document processing solutions, including classification, metadata extraction and enterprise search. Identify opportunities to improve business processes through AI and automation. Full Stack Web Development- Develop responsive web-based business applications and intuitive user interfaces for AI-powered and enterprise solutions. Collaborate with business stakeholders to design practical software solutions that improve user productivity. System Integration- Design and implement secure integrations between enterprise applications, Microsoft 365, cloud platforms and third-party SaaS solutions. Develop REST APIs and integrate AI services using Microsoft Graph, SharePoint, Teams, Azure services and other enterprise platforms. Engineering Excellence Produce secure, scalable, maintainable and well-documented software. Review, validate and optimise AI-generated code before deployment. Apply software engineering best practices, including testing, version control and CI/CD. Contribute to engineering standards and AI development best practices. 3. Critical skills and job complexity (not addressed in section 2) a) Unique knowledge and skills Essential Strong software engineering experience using C#, .NET, Python and SQL Server. Experience building modern full-stack web applications using technologies such as React, TypeScript, JavaScript, HTML5, CSS3 or equivalent frameworks. Strong experience designing REST APIs, enterprise integrations and scalable software architectures. Hands-on experience with modern AI-assisted development tools (e.g. OpenAI Codex, Claude Code, GitHub Copilot) and integrating Large Language Models (LLMs) into enterprise applications. Experience developing AI-powered applications, AI agents, intelligent automation and business workflows. Strong understanding of software architecture, design patterns and scalable application development. Strong analytical, problem-solving and communication skills, with the ability to translate business requirements into technical solutions. Desirable Experience working with cloud platforms (preferably Microsoft Azure), Microsoft 365, SharePoint and Microsoft Graph integrations. Exposure to agent frameworks (e.g. LangGraph, LangChain, Semantic Kernel or similar), Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP) concepts and AI orchestration frameworks. Experience with containerisation, DevOps, CI/CD and modern software engineering practices. b) Contact types / levels internal & external Organisation-wide c) Problem solving & decision making Analyse complex business challenges and design scalable software and AI solutions that improve business outcomes. 4. Preferred education and experience 24 years of software engineering experience, including a minimum of 2 years developing AI-powered software solutions using modern AI platforms and AI-assisted development tools. Proven experience developing enterprise software using C#, .NET, Python, modern web technologies, and REST APIs. Demonstrated ability to design, develop and deliver scalable software solutions from concept through production deployment. Experience working with Microsoft cloud technologies is highly desirable. 5. Work environment and physical demands No unusual physical work environment demands. Should be ready to travel as well as with an ability to support three different continents. 6. Competencies critical to this position Core competencies Ownership & Accountability Problem Solving Innovation & Continuous Learning Collaboration & Communication Adaptability Integrity Functional competencies AI Application & Agent Development Software Engineering & Architecture Business Automation Microsoft Cloud Technologies System Integration & Solution Design AI-First Software Engineering Software Security & Engineering Best Practices 7. Success measures Within the first 12 months, the successful candidate should: Deliver production-ready AI-powered applications that automate key business processes. Modernise and enhance the organisation's legacy .NET applications. Build reusable AI agents supporting operational, finance and investment workflows. Deliver secure integrations across Microsoft 365, cloud platforms and enterprise systems. Develop intuitive web-based applications that improve user productivity and business efficiency. Establish AI-assisted software engineering best practices and contribute to an AI-first engineering culture through the adoption of modern AI technologies (Codex, Claude Code and GitHub Copilot).