Job Title AI Technical Expert Job Description Role Summary: We are looking for a senior technology professional with 15+ years of experience in software engineering, architecture, and enterprise technology, with strong experience across data engineering, machine learning, and AI/Generative AI. The candidate will be responsible for applying AI to solve meaningful enterprise problems and realize measurable business and engineering value, while architecting and delivering scalable AI-enabled solutions and reusable AI capabilities. The role requires strong software and data engineering foundations, AI/ML expertise, system architecture, hands-on development, and technical leadership. Key Responsibilities • Identify and realize high-value enterprise opportunities through AI, with measurable business and engineering impact. • Architect and develop AI/ML and Generative AI solutions for enterprise use cases. • Build reliable data pipelines, data platforms and data processing capabilities that support AI/ML solutions. • Apply ML techniques to develop, train, evaluate and deploy machine learning solutions. • Design and develop LLM-based applications, including RAG, agents, tool use, and AI-assisted workflows. • Integrate AI solutions with existing enterprise platforms, APIs, data sources, and engineering tools. • Establish practices for AI architecture, evaluation, security, observability, and governance. • Lead POCs from hypothesis through productionisation, with measurable outcomes. • Mentor engineers and establish engineering best practices. Experience & Skills • 15+ years of software engineering / architecture / technology experience. • Strong programming skills, particularly Python, and solid software architecture fundamentals. • Experience designing data pipelines, data processing workflows, data platforms, and data quality practices. • Practical experience with ML model development lifecycle including data processing, ML model training, evaluation, deployment, and monitoring. • Strong understanding of AI/ML techniques and modern GenAI approaches, including but not limited to LLMs, prompting, context engineering and inference. • Practical experience with LLMs, RAG, AI agents, embeddings, and vector databases. • Experience with modern AI application frameworks and orchestration technologies such as LangChain, LangGraph, Semantic Kernel or equivalent. • Experience taking AI/ML solutions from PoC to production in enterprise environments. • Understanding of AI security, evaluation, observability, and governance. Experience applying AI across the software development lifecycle (SDLC), DevOps and developer productivity is highly desirable.