We are seeking an experienced and innovative IT Tech Lead to join our dynamic Tech & Data team and spearhead the development of our next-generation reinsurance systems, including their architecture and broader integration within global IT ecosystem.
Key duties and responsibilities
You have strong technical leadership and architecture skills to design and manage a scalable, secure, and resilient Azure reinsurance platform
You have full-stack delivery oversight experience across Java/Python/.NET backends and Angular/React frontends
You have strong cloud and DevOps skills using Azure, containers, AKS/ACA, and CI/CD to enable reliable releases
You lead adoption of AI-assisted development tools and generative AI practices to improve team productivity, code quality, and delivery speed
You have proven mentoring and coaching skills that build a culture of excellence, innovation, and continuous learning
You have strong stakeholder collaboration skills to translate business needs with the Solution Owner, BAs, and end users
You define practical patterns for integrating AI capabilities into enterprise applications while aligning solutions with architecture, security, and operational standards
You have a continuous improvement mindset to enhance processes, user experience, stability, and efficiency while reducing complexity
You apply responsible AI and data protection principles to ensure PII standards, security requirements, ICS controls, fairness, and explainability are maintained
You have strong problem resolution skills, including leading issue triage and root-cause analysis for critical production support.
Required experience & competencies
7+ years designing and delivering solutions, ideally insurance or financial services.
Backend Proficiency: Expert in Java Spring Boot, Spring Batch or .NET C#, preferably both. SQL Server or Postgres experience is preferred
Frontend Expertise: Strong Angular or React skills with TypeScript, HTML5, and CSS3
Cloud Native: Design and deploy on Azure, AKS hands-on experience required
AI-Assisted Development: Proven experience using AI-assisted software development tools and workflows to guide engineering teams
Generative AI Enablement: Demonstrated ability to apply generative AI to improve developer productivity, solution quality, and delivery efficiency
Responsible AI: Strong understanding of responsible AI principles, including data privacy, fairness, explainability, and secure enterprise adoption
Enterprise AI Integration: Hands-on experience defining or implementing AI capabilities within enterprise applications and delivery platform
Industry Knowledge: Experience in insurance, reinsurance, or financial services domains
Fluent in English, written and spoken.