Generative AI Director

As a Generative AI Executive Director within our Chief Technology Office (CTO), you will be responsible for leading a team of approximately 20 data scientists and engineers, overseeing the development and implementation of advanced AI and machine learning solutions. You will engage in close collaboration with cross-functional teams, including the ML Centre of Excellence, AI Research, Cloud Engineering, and others, to foster innovation and deliver solutions that yield a high Return-on-Investment (RoI). This senior leader will play a pivotal role in shaping the bank's technology strategy, ensuring alignment with business objectives, and fostering a culture of innovation and collaboration.

Job Responsibilities 

• Combines vast data assets with cutting-edge AI, including LLMs and Multimodal LLMs
• Bridges scientific research and software engineering, requiring expertise in both domains
• Leads, mentors, and inspires a team of 20 data scientists and engineers, fostering a culture of innovation and excellence
• Collaborates with senior leadership to identify opportunities for AI/ML to drive business growth and efficiency

Required qualifications, capabilities, and skills 

• Masters or PhD in a quantitative discipline, e.g. Computer Science, Mathematics, Statistics.
• Proven track record in building and leading teams of experienced ML engineers/scientists, preferably in the financial sector.
• Scalable AI Model Deployment –end-to-end ML model lifecycle management, optimizing training, inference, and monitoring for large-scale AI applications.
• Generative AI & LLM Infrastructure – knowledge of AI ecosystems for LLMs (GPT, OpenAI), optimizing data ingestion, model scaling, and performance tuning.
• Python & C++ for AI Performance – Expertise in Python & C++ for building ML pipelines, optimizing AI inference, and ensuring low-latency execution.
• Expertise in AI ready infrastructure, data engineering, modern data management skills and platforms such as Databricks, SageMaker
• Ensure the scalability, reliability, and security of AI/ML systems.
• Ability to understand and align with business expectations, and write clear and concise OKRs (Objectives and Key Results).
• Excellent grasp of computer science fundamentals and SDLC best practices.
• Ability to understand business objectives and align ML problem definition.
• Excellent communication skills to effectively convey technical information and ideas at all levels, building trust with stakeholders.

Preferred qualifications, capabilities, and skills 

• Stay abreast of industry trends and emerging technologies in AI/ML.