Head of Software Engineering

Built on meritocracy, our unique company culture rewards self-starters and those who are committed to doing what is best for our customers.

Brown & Brown is seeking a Head of Software Engineering to join our growing team in Plano, TX
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We are seeking a talented and experienced Head of Software Engineering to join the Bridge Specialty Group IT organization. Reporting to the Divisional CIO, this role will own the delivery, quality, and technical execution of our .NET, Azure-hosted application portfolio. The Head of Software Engineering will lead multiple development teams and the QA/Testing function (manual and automated), building high-quality, scalable software while championing Agile/Scrum delivery practices, modern AI-assisted engineering tools, and the development of AI-driven and agentic solutions.

This role works closely with the Head of IT Architecture, Product Owners, Enterprise Architecture, Cloud Platform, Security, and business stakeholders to translate architectural direction and business priorities into well-engineered, reliably delivered software.

• Lead, coach, and grow multiple .NET development teams, building a culture of technical excellence, accountability, and continuous improvement.
• Own the QA/Testing function, including both manual testing and automated test engineering, ensuring quality is built into the delivery lifecycle rather than bolted on at the end.
• Set clear performance expectations, provide regular feedback, and manage staffing, hiring, and workload allocation across teams.
• Partner with the Head of IT Architecture to align engineering execution with architectural standards, technology roadmaps, and enterprise direction.
• Mentor engineering managers, technical leads, and senior engineers, developing bench strength and succession within the organization.

• Champion Agile/Scrum practices across all development teams, ensuring consistent application of sprint planning, backlog grooming, estimation, retrospectives, and delivery metrics.
• Partner with Product Owners and Scrum Masters to maintain healthy, well-prioritized backlogs and predictable release cadences.
• Establish and monitor engineering delivery metrics (velocity, quality, cycle time, defect rates) and use them to drive continuous improvement.
• Remove impediments and manage cross-team dependencies to keep delivery on track.
• Ensure teams follow sound software engineering practices, including code reviews, branching strategy, and release management.
• NET & Azure Application Engineering
• Guide the design, development, and maintenance of .NET applications and services hosted on Microsoft Azure.
• Ensure engineering teams follow modern software engineering standards for maintainability, scalability, performance, and security.
• Partner with the Head of IT Architecture and Enterprise Architecture on application architecture, technical design reviews, and modernization roadmaps.
• Support CI/CD pipelines, Infrastructure as Code, and Dev Sec Ops  practices in partnership with the Cloud Platform Engineering team.
• Oversee technical debt management and prioritize remediation alongside new feature delivery.

• Drive adoption of AI-assisted development tools such as Claude Code, Git Hub Copilot, and comparable solutions across the SDLC to accelerate coding, code review, testing, and documentation.
• Establish standards, guardrails, and best practices for the safe, secure, and effective use of AI coding assistants within development and QA workflows.
• Lead the design and delivery of AI-driven and agentic solutions that integrate into existing platforms (e.g., intelligent automation, autonomous workflow agents, AI-powered features for internal and customer-facing applications).
• Maintain working familiarity with AI tools, models, and integration patterns, and evaluate how they can be applied to existing platforms and the development process itself.
• Partner with the Head of IT Architecture and business stakeholders to pilot and scale AI-driven enhancements and agentic solutions responsibly and securely.
• Educate and upskill engineering and QA teams on practical use of AI in the software development lifecycle, including AI-assisted coding, testing, code review, and agentic development patterns.
• Track measurable gains in developer productivity and delivery velocity resulting from AI tool adoption,

• Establish and enforce secure coding…