Senior Software Engineering Manager, AI Software Engineering Enablement

Established nearly two centuries ago, FM is a leading mutual insurance company whose capital, scientific research capability and engineering expertise are solely dedicated to property risk management and the resilience of its policyholder-owners. These owners, who share the belief that the majority of property loss is preventable, represent many of the world’s largest organizations, including one of every four Fortune 500 companies.

They work with FM to better understand the hazards that can impact their business continuity to make cost-effective risk management decisions, combining property loss prevention with insurance protection.

The Senior Manager, AI Software Engineering Enablement will lead FM’s transition to a governed, AI-enabled software delivery operating model.

This leader is responsible for defining, building, and scaling the enterprise capabilities that enable AI-assisted, traceable, secure, and compliant software delivery. The role oversees the adoption of modern engineering platforms, Enterprise Standards as Code, software development skills, shared services, governance automation, traceability services, release readiness, and AI-enabled development capabilities.

This leader must bring deep software engineering experience and extensive knowledge of modern engineering best practices, including software architecture, secure development, quality engineering, automated testing, code quality, maintainability, observability, delivery automation, and lifecycle governance. The leader will ensure that AI-enabled development strengthens, rather than bypasses, the engineering disciplines required to build reliable, secure, maintainable, and scalable software.

Working across Engineering, Architecture, Security, Audit, Compliance, and Platform Engineering, this leader will establish the frameworks, platforms, shared services, and governance capabilities that allow software teams to deliver consistently by leveraging AI while maintaining enterprise standards and regulatory expectations.

This is a manager-of-managers role with responsibility for teams focused on developer enablement, AI SDLC capabilities, shared services, engineering governance services, enterprise development standards, and AI software delivery platforms. The scope of impact spans software engineering efforts across FM, driving the adoption and evolution of AI-enabled software delivery capabilities throughout the enterprise.

The role is approximately 70% technical leadership and strategy and 30% organizational leadership, adoption, and stakeholder engagement.

• Own the execution and refinementof FM’s AI Software Delivery roadmap and target operating model.

• Establish and promote modern software engineering capabilities and best practices across FM, including:

• Software architecture and design

• Secure software development

• Code quality and maintainability

• Quality engineering and automated testing

• Observability and operational readiness

• CI/CD and delivery automation

• Developer productivity and experience

• Software lifecycle governance

• Establish enterprise AI software delivery capabilities, including:

• AI-Driven development

• Enterprise Standards as Code

• Development Skills

• Traceability Services

• Governance Services

• Release Readiness Services

• Enterprise Agent Platform capabilities

• Cost Management and Fin Ops

• AIDevOps capabilities, including AI integration within engineering pipelines, testing, deployment, and operational workflows

• Ensure AI-enabled development enhances engineering rigor, quality, security, and maintainability rather than bypassing established software engineering disciplines.

• Drive enterprise adoption of platform and emerging AI-enabled software engineering capabilities.

• Define the strategy, lifecycle, and governance model for reusable software development skills, agents, standards, shared services, and delivery accelerators.

• Establish metrics and measurement frameworks that quantify the value created by the AI SDLC, including productivity, quality, risk reduction, and return on investment for AI tooling and services.

• Establish architecture and operating models for enterprise agent execution, enterprise prompt and skills…