What are the responsibilities and job description for the Manager, Engineering position at Liberty Mutual Insurance Group?
Serve as a visible GenAI thought leader within GRS -- regularly presenting to engineering, business, and executive stakeholders on the state of generative AI, agentic frameworks, and emerging best practices. Champion agentic engineering techniques across the organization, driving adoption of frameworks such Spec-Driven Development. Evaluate and advocate for new GenAI technologies and patterns; lead their assessment, selection, and integration into the team's engineering practices. Translate complex technical concepts into clear, compelling narratives for both technical and non-technical audiences. Lead, mentor, and grow a team of data/software engineers, providing technical coaching and career guidance. Team includes 8 FTEs and 12 contractors. Monitor and drive team effectiveness; remove blockers, manage cross-team dependencies, and maintain a high-velocity delivery cadence Manage performance, conduct reviews, and champion professional development including stretch assignments and rotations Own hiring and recruiting, actively building a team with strong AI operators Knowledge of technology concepts, strategies and methodologies typically acquired through a Bachelor`s or Master`s Degree in technical or business discipline and a minimum of five years' experience in a practice relevant domain including delivering software solutions in an agile environment. 3 years in a leadership role preferred. Able to manage complex technology development concepts, capabilities and maturity. Requires excellent analytical ability, consultative, communication, presentation and management skills, strong judgment and ability to effectively liaise with cross functional stakeholders and optimize teams. Demonstrated ability to operate collaboratively and build consensus. In-depth knowledge of technology standards and guidelines; knowledge of management concepts, practices and techniques; thorough knowledge of business functions and operations, objectives and strategies. Experience operating with geographically dispersed engineering teams Work in close, day-to-day collaboration with data scientists from the DSS organization to align on solution design, development, and production deployment strategies Bridge the gap between data science experimentation and robust, scalable engineering delivery Establish shared goals, KPIs, and ways of working with DSS counterparts and Product Owners to ensure coherent end-to-end solution delivery