Manager, AI Engineering

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.Leadership ResponsibilitiesLead, 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 ResponsibilitiesOwn 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 ResponsibilitiesManage 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 & ExperienceRequired QualificationsMinimum: 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 Experience10 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.#J-18808-Ljbffr