Artificial Intelligence Engineer

About the RoleWe 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 ResponsibilitiesAI Solution Design & DevelopmentDesign, develop, and maintain scalable AI solutions that support both conversational (chat-based) and transactional business functionsContribute to the architecture of AI platforms that are modular and extensible, enabling adoption across multiple business units with varying requirementsEvaluate and recommend appropriate AI tools, models, frameworks, and platforms based on use case requirements and organisational standardsImplement orchestration patterns that coordinate AI agents, models, and workflows in a coherent and reliable mannerAI Integration & EngineeringBuild and maintain integrations between AI components and enterprise systems including CRM, ERP, document management, HR platforms, and communication toolsDesign and implement APIs and integration patterns that enable seamless connectivity between AI capabilities and consuming applicationsImplement Retrieval-Augmented Generation (RAG) pipelines, agentic workflows, and multi-model coordination patterns based on solution requirementsEnsure AI solutions are engineered for performance, reliability, and maintainability in production environmentsConversational & Transactional AIDevelop conversational AI capabilities including intelligent chatbots, virtual assistants, and LLM-powered dialogue systemsBuild transactional AI functions that automate or augment business processes such as document processing, data retrieval, approvals, and workflow automationSupport the design of solutions that handle both real-time and batch AI processing depending on the nature of the business use caseGovernance, Security & Responsible AIApply responsible AI principles throughout the development lifecycle including fairness, transparency, explainability, and data privacyAdhere to and contribute to AI governance practices covering model versioning, monitoring, and auditabilityEnsure AI solutions are built in compliance with organisational security policies, data handling standards, and relevant regulatory requirementsCollaborate with the Information Security team to embed appropriate controls within AI solution designTechnical Leadership & CollaborationServe as a technical lead within the AI team, providing guidance and mentorship to junior engineers and developersWork closely with solution architects, business analysts, and product owners to translate business requirements into sound technical designsParticipate in design reviews, technical discussions, and proof-of-concept evaluationsContribute to the development of internal standards, engineering guidelines, and reusable AI componentsStay current with advancements in the AI space and proactively identify opportunities to apply emerging capabilities within the organisationRequired Qualifications & ExperienceEducationBachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related technical disciplineExperienceMinimum 6–8 years of overall experience in software or AI engineeringMinimum 3–4 years of hands-on experience designing and implementing production AI solutions in an enterprise environmentProven experience working on AI platforms or solutions that span conversational and process automation use casesExperience contributing to or leading the technical delivery of AI integration projects involving multiple enterprise systemsTechnical Skills Area Required ExpertiseAI & ML FrameworksLangChain, Semantic Kernel, AutoGen, LlamaIndex, or equivalent AI orchestration frameworksLarge Language ModelsOpenAI GPT, Azure OpenAI, Anthropic Claude, Gemini, or open-source LLMs (LLaMA, Mistral)Vector DatabasesPinecone, Weaviate, Azure AI Search, pgvector, or equivalentCloud — Azure (Primary)Azure OpenAI Service, Azure AI Studio, Azure Bot Services, Azure API Management, Azure Functions, Azure Logic AppsAzure InfrastructureAzure Kubernetes Service (AKS), Azure Container Apps, Azure Service Bus, Azure Key Vault, Azure MonitorProgramming LanguagesPython (primary), with working proficiency in at least one of JavaScript, C#, or JavaAPI & IntegrationREST API design, event-driven architecture, webhook patterns, API gateway managementRAG & Knowledge RetrievalRetrieval-Augmented Generation (RAG), embedding models, semantic search, knowledge base integrationSecurity & GovernanceAI security controls, data privacy compliance, responsible AI principlesDevOps & MLOpsCI/CD pipelines, containerisation (Docker, Kubernetes), model versioning, prompt management, and monitoringPreferred QualificationsHands-on experience with the Microsoft Azure AI and integration stack, including Azure AI Studio, Azure Integration Services, and Azure API ManagementFamiliarity with agentic AI design patterns and multi-agent coordination frameworksExperience working in regulated industries such as aviation, finance, healthcare, or governmentExposure to enterprise integration platforms such as MuleSoft, Azure Integration Services, or equivalent middlewareMicrosoft Azure certifications such as Azure AI Engineer Associate (AI-102) or Azure Developer Associate (AZ-204) are an advantageFamiliarity with Power Platform (Power Automate, Power Apps) in the context of AI-assisted workflowsKey CompetenciesTechnical Depth — Strong hands-on engineering capability with the ability to move from concept to working solutionProblem Solving — Approaches complex and ambiguous technical challenges in a structured and pragmatic mannerCommunication — Able to explain technical concepts and decisions clearly to both technical peers and non-technical stakeholdersCollaboration — Works well within cross-functional teams and across business units with differing prioritiesInnovation Mindset — Actively follows developments in the AI space and brings relevant ideas and approaches to the teamOwnership — Takes responsibility for the quality and reliability of solutions developed and proactively addresses issuesMentorship — Committed to uplifting team capability through knowledge sharing and hands-on guidance