About the Company:

The company provides property and casualty insurance processing and distribution solutions, connecting agents, brokers, wholesalers, MGAs, MGUs, program administrators, carriers, and policyholders. Its software and services help improve insurance processing, customer service, and business management.

About the Role:

We are looking for an experienced Software Architect to own the architecture and technical direction of two enterprise products, ALIS Suite and Nexsure. The role involves defining engineering roadmaps, modernizing existing codebases, reducing technical debt, and improving security, scalability, reliability, and maintainability.

The ideal candidate will have strong hands-on expertise in C#, .NET, SQL Server, and enterprise application architecture, along with practical experience evaluating and implementing AI-enabled capabilities.

Key Responsibilities:

- Own the current and target architecture of ALIS Suite and Nexsure.

- Develop and execute prioritized engineering roadmaps for both products.

- Assess existing systems, dependencies, data flows, and operational risks.

- Guide application design, database evolution, API integrations, and deployment architecture.

- Establish design principles, coding standards, interface contracts, and architecture decision records.

- Review critical designs and code, mentoring teams on performance, testability, and backward compatibility.

- Improve build, testing, release, deployment, and observability practices.

- Identify and reduce technical debt, fragile integrations, database bottlenecks, and architectural risks.

- Strengthen security, authentication, authorization, data protection, resilience, and disaster recovery.

- Evaluate AI opportunities through measurable experiments, appropriate safeguards, and human oversight.

- Convert successful AI experiments into maintainable, monitored, and supportable solutions.

- Collaborate with product, engineering, security, and operations teams to balance business priorities with technical improvements.

- Communicate architectural decisions and trade-offs to technical and nontechnical stakeholders.

- Mentor engineers and technical leads while promoting shared ownership across both codebases.

Required Skills & Experience:

- Deep software architecture and hands-on engineering experience with C#, .NET, SQL Server, APIs, and enterprise applications.

- Experience modernizing established codebases while maintaining business-critical delivery.

- Cloud-native architecture experience, including containerization, horizontal scalability, and zero-downtime deployment patterns.

- Strong understanding of security, reliability, scalability, observability, and operational recovery.

- Experience evaluating architectural trade-offs and prioritizing engineering improvements.

- Ability to lead through influence, review designs, and mentor engineers across teams.

- Practical experience evaluating or delivering AI-enabled capabilities, including quality assessment, data protection, and human oversight.

- Understanding of architecture governance, engineering standards, and technical risk management.

Preferred Experience:

- Experience with insurance software, complex customer integrations, or long-lived enterprise products.

- Experience with cloud platforms, automated delivery pipelines, and data migration.

- Experience establishing architecture governance that supports engineering efficiency without unnecessary processes.

Initial Priorities:

- Assess the architecture and risks across both product codebases.

- Establish initial roadmap milestones with engineering and product leaders.

- Deliver an early improvement that enhances delivery safety or reduces a high-priority risk.

- Establish repeatable processes for architecture decisions, technical debt prioritization, and AI experiment evaluation.

Measures of Success:

- Architecture roadmaps for both products are agreed upon and translated into delivered milestones.

- Technical debt and architecture risks are reduced, with measurable improvements in reliability, security, performance, or delivery speed.

- Engineering teams consistently apply documented design standards and architecture decisions.

- AI initiatives demonstrate measurable value and are implemented safely and sustainably.