Job Description

Roles & Responsibilities

• Identify inefficiencies across organisational processes and design AI-powered or automated alternatives
• Partner with business units to deeply understand their workflows, then challenge and improve them
• Drive the design and implementation of intelligent systems that create lasting operational impact
• Continuously scan the AI landscape including new models, emerging frameworks, and disruptive tools and translate relevant information into actionable intelligence for the organisation
• Evaluate vendors, platforms, and technology partners with a critical and strategic eye
• Produce sharp, well-researched briefs to support leadership decision making
• Build compelling, rigorous business cases for AI and automation initiatives including ROI models, risk frameworks, and strategic rationale
• Present ideas to senior leadership with clarity, confidence, and conviction
• Champion the adoption of new AI tools by leading training sessions and supporting change enablement across the organisation
• Craft high-quality reports, dashboards, and executive presentations that inform and inspire

Desired Candidate Profile

• Bachelor’s degree in Computer Science, Software Engineering, Information Technology, or a related discipline

• Graduated within the last 3 years (early-career role, 0–3 years post-graduate experience

• Genuine grounding in software development, systems thinking, or data

• Certifications in AI or machine learning (e.g., Google AI, Microsoft Azure AI, IBM AI Engineering, DeepLearning AI) are strong differentiators

• Strategic and commercial instinct with familiarity in business operations, process design, or organizational dynamics

• Strong interpersonal skills to explain complex AI concepts to C-suite executives

• Polished written communication and ability to build visually coherent presentations

• Proactive, analytically sharp, adaptable, comfortable interacting with senior stakeholders in cross-functional environments

• Hands-on experience or strong curiosity demonstrated through academic projects, personal builds, open-source contributions, or self-directed learning

• Experience or familiarity with AI agent frameworks and orchestration tools such as LangGraph, LangSmith, CrewAI, Hugging Face

• Beginner to intermediate skills in multi-agent frameworks (AutoGen or equivalent), no-code/low-code automation tools (Flowise or n8n), and LLM-integrated applications (OpenAI API / Azure OpenAI)

• Basic Docker and Cloud (AWS or Azure) skills sufficient to set up and deploy applications