Job Description

Roles & Responsibilities

AI Strategy & Executive Advisory

• Serve as the trusted AI advisor to C-Level executives and senior

business leaders.

• Translate complex business challenges into practical AI transformation

strategies.

• Conduct AI maturity assessments, opportunity identification and

business value assessments.

• Develop enterprise AI roadmaps and investment strategies.

• Facilitate executive workshops and design-thinking sessions.

• Present compelling AI business cases to executive committees and

steering boards.

• Define enterprise AI operating models and governance frameworks.

• Establish Responsible AI principles aligned with global standards.

Enterprise Solution Architecture

Design scalable enterprise AI platforms including:

• Large Language Models (LLMs)

• Retrieval Augmented Generation (RAG)

• AI Agents & Agentic AI

• Multi-Agent Systems

• Multi-modal AI

• Knowledge Management Platforms

• Intelligent Search

• Enterprise Copilots

• Conversational AI

• AI Automation Platforms

Architect solutions knowledge, such as:

• Cloud-native AI platforms

• Hybrid AI environments

• Secure enterprise AI

• API-driven architectures

• Microservices

Produce:

• Solution Architecture Documents

• Technical Design Documents

• Enterprise Reference Architectures

• Integration Designs

• AI Security ModelsTechnical Delivery

Lead the development of:

• AI Proof of Concepts

• Minimum Viable Products

• Production AI Applications

• Enterprise Chatbots

• Intelligent Assistants

• Knowledge Retrieval Platforms

• Document Intelligence Solutions

• AI Workflow Automation

Hands-on responsibilities include:

• Prompt Engineering

• Model Evaluation

• Fine Tuning

• Vector Database Design

• RAG Pipeline Development

• AI Agent Development

• Model Deployment

• API Development

• AI Performance Optimisation

Machine Learning & Data Science

Lead teams developing:

• Predictive Analytics

• Classification Models

• Forecasting Models

• Recommendation Engines

• NLP Solutions

• Computer Vision

• Time Series Analysis

• Feature Engineering

• Data Preparation

• Model Validation

• Model Monitoring

AI Engineering & MLOps

Design and manage enterprise AI deployment pipelines including:

• CI/CD

• Model Registry

• Experiment Tracking

• Feature Stores

• Model Monitoring

Engage with C-suite executives

• Work alongside Enterprise Architects

• Guide Data Scientists and ML Engineers

• Mentor Development Teams

• Coordinate with Cloud Architects

• Collaborate with Cyber Security teams

• Support Project Managers and PMOs

• Lead client workshops

Desired Candidate Profile

Essential:

• Bachelor's degree in Computer Science, Software Engineering, Artificial

Intelligence, Data Science, Information Systems or a related discipline.

Preferred:

• Master's degree in Artificial Intelligence, Machine Learning, Computer

Science or Data Science.

• MBA (advantageous for senior consulting roles).

Appropriate Certifications