JOB PURPOSE
Lead the AI Engineering team in designing, developing, and operating the Bank's internal AI platform – a centralized capability layer enabling agentic AI, retrieval-augmented generation (RAG), intelligent chatbots, and other AI/GenAI use cases across business lines. Drive the exploration and responsible adoption of emerging AI technologies; establish best practices for AI product development, model governance, and platform operations; and ensure the Bank derives measurable value from its AI investments.
Key Roles & Responsibilities
Leadership Responsibilities:
- Lead, mentor, and develop a team of AI engineers; build a high-performing unit with deep expertise in AI/ML engineering, LLM integration, and platform development.
- Foster a culture of experimentation, responsible AI, and knowledge sharing; organize internal demos, hackathons, and learning sessions.
- Collaborate with the Director, IT Architecture & Engineering to align AI platform architecture with the enterprise technology roadmap.
- Act as the Bank's subject-matter expert on AI/GenAI trends; advise senior leadership on strategic opportunities, risks, and investment priorities.
Strategic Responsibilities:
- Own the vision, roadmap, and delivery of the Bank's internal AI platform – supporting capabilities including agentic AI workflows, RAG pipelines, conversational AI (chatbots/copilots), prompt management, and model orchestration.
- Continuously scan the AI/GenAI landscape for breakthrough technologies, frameworks, and models (e.g., Claude, GPT, open-source LLMs); evaluate applicability and lead proof-of-concept initiatives.
- Define and enforce AI development standards covering model lifecycle management, prompt engineering, evaluation frameworks, guardrails, and responsible AI principles.
- Establish integration patterns between the AI platform and the Bank's core banking systems, data lake, and API ecosystem.
- Drive the adoption of vector databases, embedding pipelines, and semantic search to power knowledge retrieval across the organization.
- Develop vendor and partnership strategies for AI tooling (Anthropic Claude, Azure OpenAI, AWS Bedrock, LangChain, LlamaIndex, etc.) to balance innovation with cost and risk.
Operational Responsibilities:
- Manage end-to-end delivery of AI products from ideation through production deployment; ensure robust MLOps/LLMOps pipelines for monitoring, retraining, and versioning.
- Define and track KPIs for AI platform adoption, model performance, latency, cost-per-inference, and business impact.
- Coordinate with Information Security, Risk, and Compliance to ensure AI solutions adhere to regulatory requirements, data privacy standards, and the Bank's AI governance framework.
- Manage the AI platform's cloud infrastructure, optimize compute costs, and ensure high availability and disaster recovery.
- Prepare and manage the AI engineering budget; justify investments through business-case development and ROI tracking.
- Oversee HR-related functions for the team including hiring, onboarding, performance management, and professional development.
Qualifications & Experience
Required Qualifications:
- Minimum: Bachelor's degree in a relevant field. Hands-on experience building and deploying LLM-based applications, RAG systems, or AI platforms in production environments. Experience working with Kubernetes and/or OpenShift, along with integrating or developing solutions using Claude Code and OpenAI.
Preferred Experience:
- 10 years of experience in software engineering or AI/ML engineering, with at least 3 years in a leadership role managing AI development or data science teams.
- Demonstrated experience with Claude (Anthropic), Azure OpenAI, AWS Bedrock, or equivalent enterprise AI services.
- Experience in banking or financial services is strongly preferred. Middle East experience is an advantage.
- Track record of translating emerging AI research into production-grade products that deliver measurable business value.
