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Manager, AI Engineering

Emirates Development Bank (EDB)
Dubai, UAE
other
Mid-Senior
2 months ago
AI engineeringmachine learningLLMRAGprompt engineeringMLOps
Free

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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.

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.

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.

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