Chief Technology Officer

1 day ago

Sandton, South Africa Catch Recruit Full time

Our client is developing a Software as a Service (SAAS) AI platform for enhancing actuarial work. Their mission is to revolutionize the insurance industry by making advanced models accessible and user-friendly for actuaries across life, non-life and health insurance. Position Summary They are seeking a Chief Technology Officer (CTO) to join their leadership team, who is a hands-on leader who can both strategize and dive into code when needed. The ideal candidate will drive their technological strategy, lead the engineering team, and play a crucial role in shaping the product development. This is an opportunity to be at the forefront of applying machine learning to the insurance industry. The ideal candidate will: Have a deep understanding of concurrency patterns and best practices for building responsive, scalable systems Be a strong problem-solver with the ability to navigate complex technical and business challenges Be an excellent communicator who can bridge the gap between technical and non-technical stakeholders Be highly adaptable and comfortable with the fast-paced, ever-changing environment of a startup Be an ethical leader with a strong commitment to data privacy and security Key Responsibilities The CTO will be responsible for designing systems that can handle concurrent model training, real-time data ingestion, and responsive user interfaces, leveraging asynchronous processing and efficient message passing to ensure optimal performance and user experience. Technical Leadership Develop and execute the company's technology strategy aligned with business goals Make key technology decisions, including choice of stack, architecture and third-party services Stay abreast of emerging technologies and industry trends, particularly in ML, AI and insurtech Ensure the scalability, security, and reliability of our SAAS platform Product Development Collaborate with the product team to translate business requirements into technical specifications Work closely with the product leads to build a platform to design, fit and host ML/AI models Ensure the user-friendliness and efficiency of our data upload, preprocessing and model training workflows Establish MLOps practices for efficient model development, deployment and monitoring of models built using the AI platform Ensure compliance with data protection regulations and implement robust data governance practices Architect and implement robust asynchronous processing systems and message passing workflows to ensure efficient handling of computationally intensive ML tasks and real-time data processing Team Leadership Build and lead a high-performing engineering team Establish best practices for software development, including coding standards, code reviews and testing Foster a culture of innovation, continuous learning and technical excellence Infrastructure and Security Design and oversee the implementation of our cloud infrastructure (preferably using AWS) Implement robust security measures to protect sensitive insurance data Ensure high availability and disaster recovery capabilities for our SAAS platform Financial Management Manage the technology budget effectively Make strategic decisions on build vs. buy for various components of our stack Evaluate and select vendor solutions when appropriate Qualifications Bachelor's degree in Computer Science, Data Science, or a related field; Master's degree preferred 5-10 years of experience in software development, with at least 3 years in a technical leadership role Experience in building and scaling SAAS platforms at an enterprise level Deep understanding of cloud technologies, preferably AWS or GCP Experience with backend development (preferably Python) and modern front-end web development frameworks (preferably React) Extensive experience designing and implementing asynchronous systems and message passing architectures, particularly in the context of distributed computing and ML workflows Proficiency with message brokers, queuing systems and stream processing frameworks Demonstrated ability to design and optimize high-throughput, low-latency data pipelines for real-time processing Familiarity with event-driven architectures and their application in ML systems Experience with MLOps and automated ML pipelines Knowledge of data protection regulations and security best practices Strong leadership and team management skills Excellent communication skills

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