Manager, Engineering

Description

You must be authorized to work in the United States without employer sponsorship now or in the future. We will not sponsor employment visas. Candidates who will require future sponsorship, including candidates on CPT/OPT/STEMOPT who will require future sponsorship, are not eligible to apply.

 

Remote candidates will not be considered - must be aligned to one of the locations listed and able to work a hybrid model of 2 days in office/week.

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Join the Global Risk Solutions (GRS) Global Data & Advanced Analytics organization as a Manager, Engineering, leading the Advanced Analytics and Applied AI Core team at the forefront of generative AI and predictive analytics. In close partnership with the GRS Data Science Solutions (DSS) department, your team is actively dismantling legacy business workflows and replacing them with intelligent, AI-native solutions. This is not a maintenance role — it's an opportunity to lead transformation and champion highly visible initiatives.

 

Job Summary

You will lead high-performing engineering squads designing and implementing production-grade generative AI and agentic workflow solutions. As a thought leader and hands-on manager, you will help shape how the organization adopts emerging agentic engineering techniques, influence technical direction at the leadership level, and cultivate a team culture of continuous learning and bold innovation. You will partner deeply with DSS data scientists to ensure the delivery of data-centric solutions are accurate, on time, and within budget. This team also has a few more traditional applications that require periodic enhancements.

 

Responsibilities

GenAI Thought Leadership & Technical Direction

• 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.

DSS Partnership & Cross-Functional Collaboration

• 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

 Team Leadership & Delivery

• 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

 Engineering Excellence

• Uphold high standards for code quality, security, scalability, and architecture across all team deliverables
• Advocate for the elimination of technical debt and responsible management of total cost of ownership
• Champion agile practices and a culture of iterative improvement 

Qualifications

• 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 guidelin