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.

1. 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
2. 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
3. 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
4. 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
5. 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