23 Oct
Catch Recruit
Diepsloot
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 SummaryThey 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 systemsBe a strong problem-solver with the ability to navigate complex technical and business challengesBe an excellent communicator who can bridge the gap between technical and non-technical stakeholdersBe highly adaptable and comfortable with the fast-paced, ever-changing environment of a startupBe an ethical leader with a strong commitment to data privacy and securityKey ResponsibilitiesThe 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 LeadershipDevelop and execute the company's technology strategy aligned with business goalsMake key technology decisions, including choice of stack, architecture and third-party servicesStay abreast of emerging technologies and industry trends, particularly in ML,
AI and insurtechEnsure the scalability, security, and reliability of our SAAS platformProduct DevelopmentCollaborate with the product team to translate business requirements into technical specificationsWork closely with the product leads to build a platform to design, fit and host ML/AI modelsEnsure the user-friendliness and efficiency of our data upload, preprocessing and model training workflowsEstablish MLOps practices for efficient model development, deployment and monitoring of models built using the AI platformEnsure compliance with data protection regulations and implement robust data governance practicesArchitect and implement robust asynchronous processing systems and message passing workflows to ensure efficient handling of computationally intensive ML tasks and real-time data processingTeam LeadershipBuild and lead a high-performing engineering teamEstablish best practices for software development, including coding standards, code reviews and testingFoster a culture of innovation, continuous learning and technical excellenceInfrastructure and SecurityDesign and oversee the implementation of our cloud infrastructure (preferably using AWS)Implement robust security measures to protect sensitive insurance dataEnsure high availability and disaster recovery capabilities for our SAAS platformFinancial ManagementManage the technology budget effectivelyMake strategic decisions on build vs. buy for various components of our stackEvaluate and select vendor solutions when appropriateQualificationsBachelor's degree in Computer Science, Data Science, or a related field; Master's degree preferred5-10 years of experience in software development, with at least 3 years in a technical leadership roleExperience in building and scaling SAAS platforms at an enterprise levelDeep understanding of cloud technologies, preferably AWS or GCPExperience 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 workflowsProficiency with message brokers,
queuing systems and stream processing frameworksDemonstrated ability to design and optimize high-throughput, low-latency data pipelines for real-time processingFamiliarity with event-driven architectures and their application in ML systemsExperience with MLOps and automated ML pipelinesKnowledge of data protection regulations and security best practicesStrong leadership and team management skillsExcellent communication skills
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