Manager - Senior Manager AI And Data KSA - UAE

Job Description:

Manager - Senior Manager – AI & Data

About Deloitte: When you work for us, you commit to a career at one of the largest and most prestigious professional services firms in the world. We have received numerous awards over the last few years, including Best Employer in the Middle East, and Best Consulting Firm, and the Middle East Training & Development Excellence Award.

Our Purpose

Deloitte makes an impact that matters. Every day we challenge ourselves to do what matters most—for clients, for our people, and for society. We serve clients distinctively, bringing innovative insights, solving complex challenges and unlocking sustainable growth. We inspire our talented professionals to deliver outstanding value to clients, providing an exceptional career experience and an inclusive and collaborative culture. We contribute to society, building confidence and trust in the markets, upholding the integrity of organizations and supporting our communities.

Our shared values guide the way we behave to make a positive, enduring impact:

  • Lead the way
  • Serve with integrity
  • Take care of each other
  • Foster inclusion
  • Collaborate for measurable impact
  • Role Summary

The Senior Manager – AI & Data will lead the design and delivery of complex AI and GenAI solutions for clients across public and private sectors. The role is techno‑functional, requiring strong hands‑on capability in solution architecture, AI product design, and end‑to‑end delivery of AI initiatives—from problem framing through production deployment and value realization.

This role is accountable for solution quality, technical design decisions, and delivery outcomes, and it is not just limited to advisory and oversight.

  • Key Responsibilities

AI / GenAI Solutioning & Architecture

  • Lead end‑to‑end solution design for AI and GenAI applications, including:
  • LLM‑based applications (e.g., copilots, document intelligence, chatbots)
  • Predictive and prescriptive analytics
  • Recommendation and personalization engines
  • Translate business problems into deployable AI solution architecture, covering:
  • Data ingestion and preparation
  • Model selection and evaluation
  • Application integration and APIs
  • Security, scalability, and performance considerations

AI Product & Use Case Development

  • Define and own AI product roadmaps for client engagements:
  • Use case prioritization
  • MVP definition and iteration
  • Success metrics and adoption measures
  • Guide teams on build vs. buy vs. partner decisions for models, platforms, and accelerators
  • Ensure AI solutions are designed for real‑world production use, not PoCs

End‑to‑End AI Delivery (with support of your delivery team):

  • Lead full AI project lifecycle:
    • Discovery and feasibility
    • Data readiness assessment
    • Model development and validation
    • Deployment, monitoring, and iteration
  • Establish practical delivery patterns for:
    • Model lifecycle management
    • Testing and quality assurance
    • Operational monitoring and retraining
  • Work closely with client technology teams to enable handover and long‑term operability. Guide teams for change management
  • Flag risks and dependencies on project delivery to raise concerns early during implementation
Client & Team Leadership

  • Engage directly with client stakeholders to explain trade‑offs, risks, and design decisions in business terms
  • Act as the senior technical authority on AI engagements
  • Review and sign off on solution designs and delivery outputs
  • Mentor technical teams (data scientists, ML engineers, architects) (Desirable but not mandatory)

Cloud & Platform Implementation

  • Architect and solution problem statements on cloud platforms, primarily:
    • Azure (Azure AI Services, Azure OpenAI, Azure ML)
    • AWS (Sagemaker, Bedrock) – where client context required
    • GCP (Vertex AI) – where relevant
    • This would require to think from an AI product development and deployment perspective rather than POCs for a/b tests
  • Ensure alignment with enterprise architecture and security standards
  • Apply Data Sovereignty constraints applicable in middle east while reviewing and proposing final solution architecture
  • Required Experience & Skills
Technical & Functional Expertise

  • 9 –14+ years of experience in data, analytics, or AI roles with direct delivery accountability
  • Strong understanding of:
    • Machine learning fundamentals and applied AI
    • Generative AI and LLM architectures
    • Data engineering concepts supporting AI workloads
  • Proven experience delivering production‑grade AI solutions, not just prototypes and POCs
AI & GenAI Capabilities

  • Exposure to:
    • LLM orchestration frameworks
    • Prompt engineering and retrieval‑augmented generation (RAG)
    • Model evaluation, bias, and performance considerations
  • Practical understanding of AI governance, model risk, and responsible AI considerations
Consulting & Leadership

  • Experience working in client‑facing environments
  • Ability to balance technical depth with commercial and delivery constraints
  • Strong communication skills for technical and non‑technical audiences

Cloud & Engineering (desirable)

  • Experience and exposure to at least one Hyperscaler
  • Ability to design scalable, secure AI architectures

Requirements:

Back to blog

Common Interview Questions And Answers

1. HOW DO YOU PLAN YOUR DAY?

This is what this question poses: When do you focus and start working seriously? What are the hours you work optimally? Are you a night owl? A morning bird? Remote teams can be made up of people working on different shifts and around the world, so you won't necessarily be stuck in the 9-5 schedule if it's not for you...

2. HOW DO YOU USE THE DIFFERENT COMMUNICATION TOOLS IN DIFFERENT SITUATIONS?

When you're working on a remote team, there's no way to chat in the hallway between meetings or catch up on the latest project during an office carpool. Therefore, virtual communication will be absolutely essential to get your work done...

3. WHAT IS "WORKING REMOTE" REALLY FOR YOU?

Many people want to work remotely because of the flexibility it allows. You can work anywhere and at any time of the day...

4. WHAT DO YOU NEED IN YOUR PHYSICAL WORKSPACE TO SUCCEED IN YOUR WORK?

With this question, companies are looking to see what equipment they may need to provide you with and to verify how aware you are of what remote working could mean for you physically and logistically...

5. HOW DO YOU PROCESS INFORMATION?

Several years ago, I was working in a team to plan a big event. My supervisor made us all work as a team before the big day. One of our activities has been to find out how each of us processes information...

6. HOW DO YOU MANAGE THE CALENDAR AND THE PROGRAM? WHICH APPLICATIONS / SYSTEM DO YOU USE?

Or you may receive even more specific questions, such as: What's on your calendar? Do you plan blocks of time to do certain types of work? Do you have an open calendar that everyone can see?...

7. HOW DO YOU ORGANIZE FILES, LINKS, AND TABS ON YOUR COMPUTER?

Just like your schedule, how you track files and other information is very important. After all, everything is digital!...

8. HOW TO PRIORITIZE WORK?

The day I watched Marie Forleo's film separating the important from the urgent, my life changed. Not all remote jobs start fast, but most of them are...

9. HOW DO YOU PREPARE FOR A MEETING AND PREPARE A MEETING? WHAT DO YOU SEE HAPPENING DURING THE MEETING?

Just as communication is essential when working remotely, so is organization. Because you won't have those opportunities in the elevator or a casual conversation in the lunchroom, you should take advantage of the little time you have in a video or phone conference...

10. HOW DO YOU USE TECHNOLOGY ON A DAILY BASIS, IN YOUR WORK AND FOR YOUR PLEASURE?

This is a great question because it shows your comfort level with technology, which is very important for a remote worker because you will be working with technology over time...