• Plan, execute and report on IT audits across diverse technology environments, including proprietary applications, AI-enabled platforms, and core IT infrastructure.
• Evaluate the adequacy and effectiveness of controls across the system development life cycle (SDLC), change management processes, AI/ML model implementation, data governance frameworks, and cybersecurity posture.
• Assess the integrity, transparency, and compliance of AI/ML models and intelligent systems against regulatory, ethical, and operational benchmarks.
• Apply advanced data analytics and visualization techniques using tools such as Python, SQL, and Power BI to detect anomalies, control gaps, and emerging risk trends.
• Conduct comprehensive reviews of algorithmic decision systems to ensure adherence to fairness, accountability, and regulatory requirements.
• Partner with software engineering and DevOps teams to evaluate the pipelines, code management practices, and agile development workflows, embedding governance and control rigor throughout the development lifecycle.
• Design and execute data-driven scripts to extract audit insights, identify risk signals, and translate raw data into actionable findings.
• Maintain active surveillance of evolving AI governance practices and digital ethics trends to inform audit strategy and coverage.
• Prepare clear, insightful audit reports with well-articulated findings, root cause analysis, and pragmatic recommendations tailored to technical and business stakeholders.
• Monitor technological advancements and emerging risks in AI, cloud computing, and data-centric ecosystems to support proactive and risk-responsive audit planning.

Key Skills, Knowledge, Experience and Behavioural Competencies

Academic and Professional Requirements

• Bachelor’s Degree Computer Science, Software Engineering, or a related field

Experience Required:

• Minimum years of experience 4+

Skills & Knowledge Required:

• Bachelor’s or Master’s degree in Computer Science, Information Systems, Engineering, or related discipline.
• Professional certifications preferred: CISA, CISM, CRISC, or equivalent. AI certifications (e.g., AI/ML, data science) are a plus.
• 4+ years of experience in IT auditing, software development, or technology risk.
• Proficiency in data analytics (e.g., SQL, Python, R) and audit tools (e.g., ACL, IDEA).
• Understanding of AI model governance, ethical AI principles, and algorithmic auditing.
• Familiarity with cloud computing environments (e.g., AWS, Azure) and CI/CD pipelines.