Join Verisk Catastrophe and Risk Solutions as a Full Stack Software Engineer and help build the technology that turns complex risk data into clear, actionable insights. You’ll contribute across the full development lifecycle—creating scalable backend services and intuitive user experiences with our core .NET, Angular, and AWS stack—while working alongside a collaborative engineering team that values sound fundamentals, curiosity, and continuous learning. We’re also actively integrating modern AI-assisted coding tools to streamline repetitive work, accelerate development, and help engineers expand their capabilities. If you’re an adaptable developer who enjoys solving meaningful technical challenges and is excited to grow into AI-augmented engineering workflows, this is an opportunity to make a real impact while advancing your craft.
Full-Stack Delivery: Design and build robust backend REST services and responsive Angular frontends, with a focus on clean, maintainable architecture.
Technology Transition: Learn and adapt to our core stack (.NET, Angular, AWS) utilizing team mentorship, structured onboarding, and individual AI productivity aids.
Modern Version Control: Manage codebases, track changes, and participate in thorough peer code reviews using GitHub.
AI Exploration: Experiment with and champion the use of AI tools (like Claude Code) to accelerate your own learning curve, syntax translation, and test generation
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Strong Fundamentals: Deep understanding of object-oriented programming, data structures, and architectural design patterns.
Language Agnostic: High proficiency in any major modern backend language (e.g., C#, Java, Python, Go) and any frontend framework (e.g., Angular, React, Vue).
Adaptability & Curiosity: A strong desire to pivot to a new tech stack and a proactive interest in how AI tools can enhance developer productivity.
Analytical Skills: Excellent debugging and code review habits; ability to reverse-engineer logic and spot flaws in unfamiliar codebases.
What We Offer
Standard support and time to ramp up on our specific technology stack.
Encouragement and budget to experiment with modern AI development tools.
Hybrid work model with opportunities for collaboration in a team-driven environment.
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