Lead - AI Enablement Squad

Discovery – Health| Data Science Lab

Lead – AI Enablement Squad

About Discovery

Discovery’s core purpose is to make people healthier and to enhance and protect their lives. We seek out and invest in exceptional individuals who understand and support our core purpose, and whose own values align with those of Discovery. Our fast-paced and dynamic environment enables smart, self-driven people to be their best. As global thought leaders, Discovery is passionate about innovating in order to not only achieve financial success, but to ignite positive and meaningful change within our society.

About Data Science Lab

The Group Data Science Lab (DS Lab) is expanding, and we’re looking for talented individuals to join our growing team. Our global team collaborates with partners such as Discovery Health Digital, Quantium, Risk Intelligence, and renowned institutions like the London School of Economics (LSE). Working across diverse areas—including digital, clinical, wellness, and behavioral themes—we harness terabytes of structured and unstructured data using a modern big data architecture. The DS Lab also embraces a forward-thinking approach, identifying new data sources and opportunities and leveraging the Vit.AI platform, we create scalable, fit-for-purpose solutions that serve the business well into the future. 

About AI Enablement

The AI Enablement team is the engineering engine that transforms cutting-edge data science into tangible value for our members and business. We bridge experimental AI and robust, enterprise-scale production systems, enabling scalable, reliable, and efficient AI solutions.

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.

EMPLOYMENT EQUITY   
                             
The Company’s approved Employment Equity Plan and Targets will be considered as part of the recruitment process. As an Equal Opportunities employer, we actively encourage and welcome people with various disabilities to apply.