Experience:

• 5+ years development experience across APIs, integrations, microservices, or full-stack development
• Demonstrated real-world experience supported by a portfolio of work that highlights applied skills, solution delivery, and measurable impact
• Solid experience integrating AI into workflows and systems across both low-code and high-code platforms
• Hands-on use of AI coding assistants and autonomous software engineering agents
• Exposure to DevOps practices, CI/CD pipelines, infrastructure-as-code, and cloud platforms such as Azure or AWS in highly regulated enterprise environments
• Extensive experience with source control and version management systems

Qualification:

• Degree in Computer Science, IT, Engineering, or a related discipline (or equivalent practical experience)
• Professional certifications in AI Fluency or specialised AI / ML technologies

Additional responsibilities:

• Mentor and support both technical and non-technical staff
• Act as AI subject matter expert for engineering, testing, architecture teams, and business functions
• Deliver demos, internal evangelism, and produce reference documentation
• Nurture the wider internal community, helping uplift AI adoption and responsible, high-value usage across the business
• Lead the design and documentation of AI-enabled solutions
• Collaborate with delivery teams throughout the project lifecycles
• Develop internal best practices for prompt engineering, AI-processed data handling, AI-assisted coding, creation and sharing of custom agents, and responsible AI usage
• Contribute to AI governance, ethics, compliance, and risk control activities
• Ensure AI solutions comply with enterprise architecture principles, security policies, data governance standards, human-in-the-loop controls, and regulatory requirements
• Monitor and mitigate AI risks

More skills:

AI, ML and LLM concepts, Prompt engineering, prompt grounding, iterative loop techniques, context windows, embeddings, RAG, agentic workflows, Agentic AI patterns, Low-code/no-code automation platforms (e.g., Power Automate, n8n, Workato), OpenAI and Anthropic, LangChain or Microsoft Agent Framework, .NET (C#), Python, or TypeScript, AI observability practices, Model Context Protocol (MCP) servers

Other:

• Exposure to RAG, vector databases, embeddings, and AI retrieval systems
• Experience working with cloud AI services and orchestrating AI agents