Lead - AI Enablement Squad at Discovery Limited

Key Purpose

• The AI Lead is responsible for translating cutting-edge data science into robust, scalable production systems. This role leads a multidisciplinary team focused on the productionisation of machine learning and LLM models, ensuring operational excellence, technical innovation, and strategic alignment with business goals. Success in this position requires architecting and implementing production-grade systems that are scalable, maintainable, resilient, and integrated with existing production systems.

Key outputs

The successful applicant will be responsible for but not limited to the following job functions:

Areas of responsibility may include but not limited to

Team Leadership & Delivery Management

• Lead and mentor a cross-functional squad of engineers, developers, analysts, and data scientists.
• Drive agile delivery practices, ensuring timely and high-quality deployment of AI solutions.

Technical Strategy & Architecture

• Own the technical roadmap for AI productionisation, including MLOps, LLMOps, and scalable infrastructure.
• Oversee architectural decisions for model deployment, data pipelines, and cloud-native solutions.

Operational Excellence

• Implement monitoring, alerting, and incident response for AI systems in production.
• Champion best practices in CI/CD, testing, and observability for ML and LLM models.

Stakeholder Engagement

• Collaborate with data science teams to translate prototypes into production-ready applications.
• Liaise with platform and infrastructure teams to ensure seamless integration and scalability.

Strategic Impact

• Influence the velocity and reliability of AI delivery across the organisation.
• Represent the AI Enablement team in strategic forums and contribute to group-wide innovation.

Personal Attributes and Skills

The successful candidate would need to have the following competencies:

• Collaborative mentor with a natural inclination to share knowledge.
• Pragmatic and results-driven, focused on delivering robust solutions.
• Intellectually curious with a passion for technology and innovation.
• Excellent communicator, able to articulate complex technical ideas clearly.
• Ownership mindset with resilience and adaptability.

Education and Experience

The following requirements are Essential:

• Master’s degree in computer science, Engineering, or related field.
• 12+ years in software/data engineering or AI productionisation.
• Advanced proficiency in Python, SQL, cloud-native development, and MLOps/LLMOps tools.
• Experience with CI/CD, containerisation (Docker, Kubernetes), and infrastructure-as-code.

The following requirements are advantageous:

• Postgraduate qualification in AI, Data Science, or Systems Engineering.
• Familiarity with Vertex AI, BigQuery, Cloud Composer, Kubeflow.