Group Generative AI Specialist

Purpose of the Job

Quintet Private Bank  is a leading private bank in the wealth management sector; we are committed to our clients and their families, and pride ourselves on our personalised service based on a deep understanding of what clients want to achieve. We are a bank headquartered in Luxembourg with branches in Belgium, Denmark, Germany, and the Netherlands, as well as a subsidary in the UK. Supervised by the CSSF we have the ambition to stay true to our purpose to be the most trusted fiduciary of family wealth.

When you join us you are joining a company that values diversity of background, equal access to opportunities, career development, collaboration and inclusiveness. We want our employees to feel proud of being part of a company that is committed to do the right thing. You will have the opportunity to grow your career while developing personally and professionally through various resources and programmes.

Translate use-cases in and across different businesses and functions into scaleable GenAI solutions and closely work with IT in providing the best-fit GenAI tools.

Key Accountabilities

• Design, build and deploy AI-powered applications, workflows and agents that improve the effectiveness of private banking teams and enhance the client experience.                            


• Own solutions end-to-end, from problem definition and specification through architecture, implementation, deployment, monitoring and continuous improvement.                            


• Establish robust evaluation frameworks, benchmarks and error-analysis processes to improve the reliability, predictability and trustworthiness of AI systems.                                


• Engineer AI systems that meet the security, privacy, auditability and compliance standards required within a regulated European private banking environment.                                


• Use coding agents effectively by providing clear specifications, managing context, defining verifiers and orchestrating multi-agent workflows to accelerate delivery.                            


• Translate business, client and regulatory requirements into precise technical specifications and influence product decisions on what should and should not be built.                        


• Apply deep understanding of private banking, wealth management and regulatory requirements to ensure solutions are relevant, practical and client-centric.                                


• Make informed engineering trade-offs across accuracy, latency, cost, scalability, resilience, security and user experience, and communicate those decisions clearly.                        


• Rapidly prototype and validate new opportunities while balancing experimentation with the controls required for client trust, operational resilience and regulatory compliance.                  


• Continuously improve team effectiveness by evolving development practices, evaluation methods, coding-agent workflows and AI engineering standards as tools and technologies mature.

Knowledge and Experience

• Further professional Education (Masters / Professional qualification)    


• Between 3 and 5 years experience in a similar role

Attributes and Qualities

• Collaborative Teamwork                            


• Communication (Verbal & Written)                    


• Strategic & Innovative Thinking                        


• Client-Centric Mindset                            


• Results Orientation

Technical Skills

• Deep practical understanding of LLMs, context engineering, RAG, agentic workflows, tool use, memory architectures and modern AI application patterns. and ability to design and deploy production-grade AI applications rather than only experiment with models.            


• Ability to design evaluation frameworks, benchmarks, guardrails and error-analysis processes that improve AI system predictability, reliability and auditability, underpinned by strong understanding of AI risk, model governance and controls required for regulated environments.


• Strong experience with Azure, Kubernetes, Docker, APIs, cloud-native architectures and distributed systems, with ability to design secure, scalable and resilient AI platforms.                    


• Deep knowledge of software architecture, testing strategies, data stores, security, privacy, observability, reliability and scalability, backed by strong engineering judgement and ability to make clear technical trade-offs. 


• Proven ability to use coding agents effectively through context management, specification writing, verifier design, evaluation loops and multi-agent orchestration, backed by strong understanding of agent limitations and strategies for reliable human oversight.

Languages Skills

• Fluent in English