Artificial Intelligence Engineer

About the Role

We are seeking a highly skilled and experienced Senior AI Engineer / Technical Lead to join our growing AI & Digital Innovation team. The successful candidate will play a central role in the design and development of enterprise-grade AI solutions, with a focus on building scalable, extensible platforms that support both conversational and transactional AI capabilities across multiple business functions.

This is a hands-on technical role suited to an engineer who combines deep AI implementation experience with the ability to lead technically, influence architecture decisions, and collaborate effectively with cross-functional teams. The ideal candidate is passionate about applied AI, has a strong engineering foundation, and has demonstrated experience delivering AI solutions in complex enterprise environments.

Key Responsibilities

AI Solution Design & Development

• Design, develop, and maintain scalable AI solutions that support both conversational (chat-based) and transactional business functions
• Contribute to the architecture of AI platforms that are modular and extensible, enabling adoption across multiple business units with varying requirements
• Evaluate and recommend appropriate AI tools, models, frameworks, and platforms based on use case requirements and organisational standards
• Implement orchestration patterns that coordinate AI agents, models, and workflows in a coherent and reliable manner

AI Integration & Engineering

• Build and maintain integrations between AI components and enterprise systems including CRM, ERP, document management, HR platforms, and communication tools
• Design and implement APIs and integration patterns that enable seamless connectivity between AI capabilities and consuming applications
• Implement Retrieval-Augmented Generation (RAG) pipelines, agentic workflows, and multi-model coordination patterns based on solution requirements
• Ensure AI solutions are engineered for performance, reliability, and maintainability in production environments

Conversational & Transactional AI

• Develop conversational AI capabilities including intelligent chatbots, virtual assistants, and LLM-powered dialogue systems
• Build transactional AI functions that automate or augment business processes such as document processing, data retrieval, approvals, and workflow automation
• Support the design of solutions that handle both real-time and batch AI processing depending on the nature of the business use case

Governance, Security & Responsible AI

• Apply responsible AI principles throughout the development lifecycle including fairness, transparency, explainability, and data privacy
• Adhere to and contribute to AI governance practices covering model versioning, monitoring, and auditability
• Ensure AI solutions are built in compliance with organisational security policies, data handling standards, and relevant regulatory requirements
• Collaborate with the Information Security team to embed appropriate controls within AI solution design

Technical Leadership & Collaboration

• Serve as a technical lead within the AI team, providing guidance and mentorship to junior engineers and developers
• Work closely with solution architects, business analysts, and product owners to translate business requirements into sound technical designs
• Participate in design reviews, technical discussions, and proof-of-concept evaluations
• Contribute to the development of internal standards, engineering guidelines, and reusable AI components
• Stay current with advancements in the AI space and proactively identify opportunities to apply emerging capabilities within the organisation

Required Qualifications & Experience

Education

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related technical discipline

Experience

• Minimum 6–8 years of overall experience in software or AI engineering
• Minimum 3–4 years of hands-on experience designing and implementing production AI solutions in an enterprise environment
• Proven experience working on AI platforms or solutions that span conversational and process automation use cases
• Experience contributing to or leading the technical delivery of AI integration projects involving multiple enterprise systems

Technical Skills Area Required Expertise

AI & ML Frameworks

LangChain, Semantic Kernel, AutoGen, LlamaIndex, or equivalent AI orchestration frameworks

Large Language Models

OpenAI GPT, Azure OpenAI, Anthropic Claude, Gemini, or open-source LLMs (LLaMA, Mistral)

Vector Databases

Pinecone, Weaviate, Azure AI Search, pgvector, or equivalent

Cloud — Azure (Primary)

Azure OpenAI Service, Azure AI Studio, Azure Bot Services, Azure API Management, Azure Functions, Azure Logic Apps

Azure Infrastructure

Azure Kubernetes Service (AKS), Azure Container Apps, Azure Service Bus, Azure Key Vault, Azure Monitor

Programming Languages

Python (primary), with working proficiency in at least one of JavaScript, C#, or Java

API & Integration

REST API design, event-driven architecture, webhook patterns, API gateway management

RAG & Knowledge Retrieval

Retrieval-Augmented Generation (RAG), embedding models, semantic search, knowledge base integration

Security & Governance

AI security controls, data privacy compliance, responsible AI principles

DevOps & MLOps

CI/CD pipelines, containerisation (Docker, Kubernetes), model versioning, prompt management, and monitoring

Preferred Qualifications

• Hands-on experience with the Microsoft Azure AI and integration stack, including Azure AI Studio, Azure Integration Services, and Azure API Management
• Familiarity with agentic AI design patterns and multi-agent coordination frameworks
• Experience working in regulated industries such as aviation, finance, healthcare, or government
• Exposure to enterprise integration platforms such as MuleSoft, Azure Integration Services, or equivalent middleware
• Microsoft Azure certifications such as Azure AI Engineer Associate (AI-102) or Azure Developer Associate (AZ-204) are an advantage
• Familiarity with Power Platform (Power Automate, Power Apps) in the context of AI-assisted workflows

Key Competencies

• Technical Depth — Strong hands-on engineering capability with the ability to move from concept to working solution
• Problem Solving — Approaches complex and ambiguous technical challenges in a structured and pragmatic manner
• Communication — Able to explain technical concepts and decisions clearly to both technical peers and non-technical stakeholders
• Collaboration — Works well within cross-functional teams and across business units with differing priorities
• Innovation Mindset — Actively follows developments in the AI space and brings relevant ideas and approaches to the team
• Ownership — Takes responsibility for the quality and reliability of solutions developed and proactively addresses issues
• Mentorship — Committed to uplifting team capability through knowledge sharing and hands-on guidance