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https://bayt.page.link/5F9UnMv3RgtT2DLB8
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Manager, AI Engineering

26 days ago 2026/06/02
Full time · Management
500 Employees or more

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Job description

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.



This job post has been translated by AI and may contain minor differences or errors.

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