Head of AI Division

Position Purpose

To ensure the strategic implementation and scaling of artificial intelligence solutions to achieve the company’s business goals, improve process efficiency, create new revenue streams, and establish an AI-first culture.

Key Responsibilities

1. Strategic leadership and AI transformation
Developing and executing a comprehensive AI strategy aligned with business objectives and the Bank’s digital transformation strategy. Defining a strategic roadmap for implementing intelligent solutions and managing their lifecycle from idea to production-scale deployment.

2. Portfolio and demand management
Prioritizing and balancing the AI project portfolio (PoC / MVP / Scaling) based on business impact. Integrating AI components into the Bank’s overall demand management system to ensure seamless collaboration between business and technology teams.

3. AI integration into business processes and customer experience
Implementing machine learning and Generative AI solutions across key domains: risk, sales, operations, and customer services. Focusing on scalable solutions that deliver measurable value to both customers and the Bank.

4. AI/Data platforms and architecture development
Defining requirements and development direction for modern data and AI platforms that enable reuse of models and data across use cases. Coordinating integration of AI services with core banking systems for real-time operations.

5. AI governance and risk management
Building an end-to-end AI lifecycle management system in line with international standards and regulatory requirements (including the EU AI Act). Managing algorithm-related risks: bias control, model drift, explainability, and data protection.

6. Monetization and business performance
Owning key performance indicators: ROI of initiatives, revenue uplift, cost optimization, and customer retention. Evaluating results to inform decisions on scaling or discontinuing projects.

7. AI culture and talent development
Building an internal learning ecosystem (AI Academy) and AI literacy programs. Promoting a data-driven culture and encouraging AI adoption across teams.

8. C-level collaboration and change management
Establishing strong partnerships with top management and business leaders to align priorities. Providing transparent expert reporting to the Bank’s Board and supporting organizational change initiatives.

Key Requirements

• Higher education in IT, computer science, applied mathematics, finance, or related fields
• 5+ years of experience in data, IT, AI, or software engineering
• 3+ years in leadership roles
• Experience managing the full lifecycle of data products and AI solutions
• Hands-on experience with LLMs, autonomous agent systems, and modern neural network training approaches
• Experience with cloud ML services (AWS SageMaker, Azure AI, Databricks) and workflow orchestration tools (Airflow, Kubeflow)
• Deep understanding of the machine learning lifecycle
• Knowledge of scalable AI system architecture
• Experience with modern data processing technologies (Spark, Airflow, Kafka, Dask)
• Understanding of AI regulations (EU AI Act), data protection standards (GDPR), and responsible AI principles
• Understanding of data governance strategies to ensure data quality and ethical AI usage
• End-to-end understanding of model lifecycle: data collection, feature engineering, deployment, monitoring bias and drift (MLOps / LLMOps / GenAI)
• Practical knowledge of SDLC, CRISP-DM, and AI lifecycle (AILC)

Soft skills:

• Strategic thinking: ability to prioritize AI initiatives based on business impact
• Leadership and communication: ability to explain complex AI concepts in business terms and manage stakeholder expectations
• Change management: experience implementing new technologies in corporate environments and overcoming resistance
• English level: Upper-Intermediate (B2)