AI Enablement Leader

Wells Fargo•Irving, TX

31d

About The Position

Are you ready to transform how AI powers one of the world's leading financial institutions? Wells Fargo is seeking an AI Enablement Leader-a been there, done it candidate with proven accomplishments who thrives on complexity, influences at scale, and delivers intelligent solutions that matter. This is your chance to drive innovation, shape enterprise data technology strategy, and lead a team building next-generation AI capabilities for the Chief Data Office. You'll bring seasoned expertise and comprehensive understanding of data engineering and/or data management with hands-on experience in leveraging new technologies to build innovative solutions. The successful candidate will have a deep expertise in AI Automation, GenAI, Agentic, and Machine Learning solutions, along with experience in architecting AI solutions that align with responsible principles and enterprise business objectives. As our AI Enablement Leader, you'll be at the forefront of Wells Fargo's AI evolution-overseeing the planning, development, and deployment of advanced AI solutions that meet rigorous security, risk, and performance standards. You'll champion modernization and cutting-edge methodologies like retrieval-augmented generation (RAG) and agentic workflows in generative AI applications.

Requirements

8+ years of Technology Strategic Leadership experience (or equivalent through work, training, military, or education)
8+ years of Data Management and/or Data Engineering experience
8+ years of experience in data, analytics, or AI roles, with at least 5 years in leadership positions driving strategic technology initiatives.
4+ years of management or leadership experience.
8+ years of Business Execution, Implementation, or Strategic Planning experience, including Management or leadership experience, or equivalent experience demonstrated through one or a combination of the following: work experience, training, military experience, education
5+ years of Product Management experience with exposure to AI/automation
5+ years of experience working with technology teams to build and launch products in market
5+ years of experience owning/driving roadmap strategy and definition
Full stack technology expertise, including Oracle, MongoDB, Python, Java and React
Proven track record in developing and executing AI or advanced analytics strategies at the enterprise level.
Strong understanding of AI/ML technologies, platforms, and their business applications.
Ability to translate complex technical concepts into business value and actionable plans.

Nice To Haves

4+ years with agile methodologies
Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Business, or related field. Advanced degree preferred
4+ years in financial services.
7+ years of engineering experience.
3+ years in hands-on data innovation.
1+ year experience with RAG and agentic workflows in generative AI.
Experience in building and driving adoption of new tools
Knowledge of AI/ML technologies, libraries, and tools.
Familiarity with AI and ML frameworks and capabilities including PyTorch, TensorFlow, MCP, Langchain, Langraph
Understanding of MLOps practices and performance tuning for AI workloads
Industry experience in AI/GenAI and Document Intelligence AI from idea generation to implementation
Experience leading the AI charter for large tech/fintech organizations
Experience deploying production AI systems at scale in cloud environments.
Mission-aligned: shares Wells Fargo's vision of transforming the employee experience through generative AI.
Demonstrated ability to balance technical excellence with business priorities.
Strong experience collaborating with product and business stakeholders to deliver valuable and user-centric solutions.
Strong problem solving and decision-making skills with attention to detail and accuracy
Ability to work effectively across large, complex organizational levels, where flexibility, collaboration, and adaptability and partnership building are critical
Demonstrated success in leadership roles, including team building and management.
4+ years of agile methodologies (Scrum, SAFe, Kanban).
4+ years of financial services experience.
7+ years of engineering experience, or equivalent as previously described.
3+ years of comprehensive understanding of data engineering and/or data management with hands-on experience in leveraging new technologies to build innovative solutions.
1+ years' experience with retrieval-augmented generation (RAG) and agentic workflows in generative AI applications.

Responsibilities

Lead & Inspire: Manage a team of engineers and leads, driving enterprise data priorities and fostering a culture of innovation.
Shape Strategy: Build actionable roadmaps, influence business and technology leaders, and identify opportunities for continuous improvement both within the Chief Data Office and as an enabler to all lines of business, to support and accelerate their AI strategies
Deliver Excellence: Ensure software craftsmanship, security, resilience, and scalability across all AI solutions.
Drive Innovation: Encourage adoption of emerging technologies and best practices for AI model development, deployment, and monitoring.
Collaborate at Scale: Partner with architects, senior engineers, and external agencies to align with enterprise strategies and regulatory standards.
Collaborate and consult with executive leadership, stakeholders, project leads, sponsors, and business partners to clarify and define project requirements
Oversee the end-to-end execution of AI initiatives, from ideation through implementation and scaling, using best practices in project management and change enablement.
Engage with executive sponsors, business unit leaders, and technology partners to identify high-impact AI opportunities and build consensus for investment and adoption.
Enforce standards for responsible AI, including model governance, bias mitigation, transparency, and compliance with regulatory requirements.
Own Risk & Resources: Set risk management guidelines, oversee financial planning, and develop strategies for hiring top engineering talent.
Build and mentor a high performing team of AI/ML, engineering and data professionals, fostering a culture of Innovation and Excellence.
Stay at the forefront of AI trends, technologies and best practices and assess their applicability to Chief Data Office. Promote a culture of experimentation, innovation, and scalable adoption of new AI capabilities.
Managing vendor relationships to align external capabilities with internal goals.
Deliver AI solutions that drive revenue growth, cost reduction and risk mitigation.
Establish metrics and measurement frameworks to quantify AI business impact.