AI Engineer

AI Engineer

Responsibilities
 •   Strategic AI Tooling Roadmap: Development and implementation of a company-wide AI tool strategy for the tech cluster — including decisions on when to deploy GitHub Copilot, Cursor, cloud services, or on-premise solutions based on developer needs
•    Efficiency & Workflow Optimisation: Design of architectures and best practices to eliminate redundant AI calls and actively manage exponential API cost growth
•    Business-to-Central Liaison: Primary contact between business units and central functions; identifying AI-related requirements and translating them into concrete, deliverable AI solutions
•    Enablement & Change Management: Continuous needs analysis, coordination with the training department, and ensuring tailored AI training programmes are delivered in line with business requirements
 
Required Qualifications
 
•    Several years of solid, hands-on software development experience
•    Hands-on proficiency with modern AI development environments — in particular Cursor and GitHub Copilot Enterprise — and code assistants
•    Deep understanding of LLMs and AI architectures: practical experience building or deploying multi-agent systems (e.g. Anthropic / Claude, AutoGPT, LangChain) and with RAG (Retrieval Augmented Generation)
•    Security and compliance mindset: solid understanding of data classification, IP leakage risks, and responsible AI deployment
•    High self-motivation and pioneering spirit; ability to work independently and take ownership in an evolving AI landscape
•    Strong communication skills, business acumen, and the ability to explain complex AI concepts to non-technical stakeholders
1.    ?  Experience in regulated or safety-critical R&D environments is a strong advantage