Manager - Senior Manager | AI & Data Deloitte

1. 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.

2. 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)

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

3. 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