Principal AI Engineer

Working closely with business stakeholders and product teams, the Principal AI Engineer provides hands-on technical leadership and is accountable for the technical quality of assigned AI initiatives while promoting technical excellence, best practices, and innovation across the organization.

• Design, develop, and deploy AI and advanced analytics products that address high-value business challenges across the P&C business.

• Drive the end-to-end implementation of machine learning, generative AI, and data science solutions from experimentation to production.

• Collaborate with business, product, and technology stakeholders to translate requirements into robust and scalable solutions.

• Apply and promote best practices in model development, software engineering, MLOps, testing, and AI product lifecycle management.

• Provide technical guidance, mentoring, and peer reviews to Data Scientists and Machine Learning Engineers, helping raise engineering and modelling standards across the team.

• Contribute technical expertise to complex initiatives and support innovation through experimentation with emerging AI technologies.

• Ensure solutions meet performance, reliability, governance, and responsible AI standards.

Experience and Skills

• At least 8 years of experience designing, developing and deploying AI, machine learning and advanced analytics solutions in production environments.
• Strong expertise in machine learning, generative AI, statistical modelling and software engineering.
• Proven experience developing and maintaining production-grade AI products, applications and services.
• Advanced experience in model validation, performance evaluation, interpretability, and the identification and mitigation of model limitations and bias.
• Strong programming skills in Python, including object-oriented programming, API development and frameworks such as FastAPI.
• Experience building AI solutions on cloud platforms, preferably Microsoft Azure.
• Strong understanding of AI industrialization practices, including MLOps, model packaging, CI/CD, testing, deployment and monitoring.
• Experience with cloud-native technologies, including Kubernetes, PostgreSQL, and cloud storage services.
• Ability to solve complex technical problems and deliver robust, scalable and maintainable solutions from concept to production.
• Strong communication and collaboration skills and ability to work effectively in multidisciplinary teams.
• Experience with Databricks and Palantir Foundry is a strong plus.

Education

• Master’s degree in Science, Technology, Engineering, Mathematics, Computer Science, Actuarial Science or similar quantitative field