AI Enterprise Architect

AI in this role

ml-ops

Job Purpose:

This role sits with FAB’s AI Hub Innovation team and AI Enterprise Architect is responsible for designing, governing, and evolving the AI Innovation Hub AI architecture of the solutions, ensuring alignment with business strategy, goals, technology standards, and regulatory requirements.

Key Responsibilities:

Responsible for producing the Architecture Artifacts such as Architecture Decision Records (ADR) and Solution Architecture Design (SAD).
Define and maintain the enterprise AI architecture, ensuring alignment with business goals, technology standards, and regulatory requirements
Lead the evaluation, selection, and adoption of AI technologies, platforms, and tools across the initiatives.
Develop and enforce architectural standards, best practices, and governance frameworks for AI initiatives
Collaborate with business, data, and technology teams to design end-to-end AI solutions that are scalable, secure, and cost-effective
Oversee integration of AI/ML models into production systems, ensuring reliability, performance, and maintainability
Guide architects, engineers, and scientists on application strategy, model lifecycle management, and MLOps practices

Requirements / Qualifications:

5+ years of experience in enterprise architecture, with a strong focus on AI, data, or advanced analytics in large-scale environments
Proven track record in designing and implementing AI/ML platforms, frameworks, and reference architectures at enterprise scale
Deep understanding of AI/ML lifecycle, including data engineering, model development, deployment, monitoring, and governance
Expertise in cloud-native architectures, hybrid/multi-cloud strategies, and integration of AI solutions with existing enterprise systems
Strong knowledge of data privacy, security, and regulatory compliance (e.g., GDPR, local data laws) as they relate to AI
Ability to translate business strategy into AI architecture roadmaps and actionable blueprints
Excellent communication and stakeholder management skills, with the ability to influence both technical and non-technical audiences
Educational qualifications: Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field; relevant certifications (e.g., TOGAF, AWS/Azure Architect, AI/ML certifications) are preferred

Preferred / Beneficial:

Experience in banking or other highly regulated industries preferred

How we rate this

AI Enterprise Architect at First Abu Dhabi Bank rates 69 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

ML Ops

Questions you could be asked

How do you monitor a model once it's live, and how do you know it needs retraining?
Describe a typical day in a role like this one: which parts run through AI directly?
If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

List these exact terms on your resume: ML Ops. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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