Gen AI Engineering Senior Director

Gen AI Engineering Senior Director

At U.S. Bank, we're on a journey to do our best. Helping the customers and businesses we serve to make better and smarter financial decisions and enabling the communities we support to grow and succeed. We believe it takes all of us to bring our shared ambition to life, and each person is unique in their potential. A career with U.S. Bank gives you a wide, ever-growing range of opportunities to discover what makes you thrive at every stage of your career.

Try new things, learn new skills and discover what you excel at—all from Day One.

The Gen AI Engineering Senior Director leads the strategy, architecture, and delivery of enterprise-scale AI platforms, including GenAI, machine learning, and agentic AI capabilities. This role is responsible for building and scaling secure, resilient, and high-performing platforms that enable enterprise-wide AI adoption. The Director oversees multiple engineering teams and leaders, ensuring strong execution, operational discipline, and alignment with enterprise standards for risk, compliance, and responsible AI.

Key Responsibilities

• Lead the vision, architecture, and roadmap for enterprise AI platforms, including GenAI, LLM integration, Retrieval-Augmented Generation (RAG), and AI-driven search.
• Provide technical leadership across multiple engineering teams; develop engineering managers and senior engineers while establishing standards, guardrails, and governance models.
• Own cloud-native platform design and delivery across Azure and AWS, ensuring scalability, reliability, performance, and cost optimization.
• Oversee MLOps and production operations, including CI/CD pipelines, model deployment, monitoring, evaluation, and lifecycle governance.
• Ensure alignment with enterprise requirements for security, data privacy, compliance, and Responsible AI practices.
• Drive cross-functional collaboration with product, risk, security, and business stakeholders to enable secure and scalable AI adoption.

Operational Leadership & Execution Discipline

• Maintain strong awareness of team delivery, technical issues, and platform risks; step in to review designs, code, and architectural decisions as needed.
• Ensure Agile practices are consistently followed, including sprint planning, backlog refinement, and delivery tracking.
• Enforce operational rigor across teams, including keeping Jira artifacts current, transparent, and aligned to priorities.
• Provide ongoing feedback on team performance, resource allocation, and organizational effectiveness to optimize delivery outcomes.
• Manage core people leadership responsibilities, including addressing HR-related matters, supporting employee development, and ensuring team engagement.
• Ensure continuity of delivery through appropriate backup coverage, resource planning, and support during team member absences.
• Oversee administrative responsibilities such as time tracking and compliance with enterprise processes (e.g., timesheets, reporting).
• Continuously identify and drive improvements to increase team velocity, reduce friction, and accelerate platform delivery.

Basic Qualifications
- Bachelor's degree, or equivalent work experience - 10 or more years of relevant software engineering experience
- Six or more years of experience leading multiple software engineering teams

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
• Minimum 5 years of experience managing engineering teams, including direct oversight of engineering managers and senior technical staff.
• 10+ years of experience in software engineering, platform engineering, or related disciplines.
• Proven experience designing and delivering large-scale, distributed systems and cloud-native platforms (Azure and/or AWS).
• Working knowledge of AI/ML and GenAI concepts, including familiarity with LLMs, RAG architectures, and AI application integration (deep specialization not required).
• Familiarity with MLOps practices, including CI/CD concepts for models, monitoring, and lifecycle considerations.
• Experience implementing enterprise-grade security, compliance, and data governance frameworks.
• Demonstrated ability to influence and…