Job Description

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.