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.