Principal Engineer - AI Enablement & Adoption

Wells Fargo Bank•Iselin, NJ

3d•Hybrid

About The Position

Wells Fargo is seeking a Principal Engineer, AI Enablement & Adoption to accelerate the responsible, practical adoption of artificial intelligence across the organization. This highly visible role combines AI engineering, technical enablement, learning, and adoption. The role defines and executes Technology’s AI learning and development strategy while creating AI solutions, technical content, reusable resources, and demonstrations. The Principal Engineer delivers hands-on training and partners with teams to turn emerging AI capabilities into practical business outcomes. The ideal candidate is a builder, educator, and technical influencer who can make complex AI concepts accessible and help teams progress from awareness to experimentation, implementation, and adoption. The role provides strategic technical leadership while remaining hands-on in AI technologies and solution development. It includes designing and building AI, Generative AI, Agentic AI, automation, and intelligent workflow solutions; creating reusable assets and implementation guidance; delivering workshops and training to technical and business audiences; and advising teams on emerging technologies, their capabilities, limitations, risks, and suitable applications. The Principal Engineer collaborates across engineering, architecture, product, cybersecurity, risk, governance, and business teams to enable responsible AI implementation and scalable adoption.

Requirements

7+ years of engineering experience, or equivalent demonstrated through work experience, training, military experience, education, or a combination of these.
7+ years of experience leading large-scale transformation, Learning & Development, Organizational Effectiveness, change management, adoption, and workforce enablement programs across multiple organizations.
4 years of experience supporting Artificial Intelligence (AI), Generative AI (GenAI), data, or emerging technology initiatives.

Nice To Haves

Experience designing, developing, or implementing Generative AI, Agentic AI, intelligent automation, or other emerging technology solutions.
Experience creating and delivering technical learning content, workshops, demonstrations, hackathons, enablement programs, or hands-on training.
Hands-on programming or solution development experience using Python, Java, C#, C++, or comparable programming languages.
Experience with AI agents, prompt and tool design, retrieval-augmented generation (RAG), orchestration, model evaluation, observability, and human-in-the-loop solutions.
Experience with enterprise AI and automation platforms such as Microsoft AI technologies, Copilot Studio, Power Automate, UiPath, or comparable platforms.
Experience developing proofs of concept, prototypes, reusable technical assets, reference implementations, and solution demonstrations.
Experience supporting technology adoption through technical coaching, enablement, implementation guidance, and change-focused activities.
Experience evaluating emerging technologies and translating findings into practical engineering or adoption recommendations.
Knowledge of responsible AI practices, including security, data protection, access management, testing, auditability, governance, and human oversight.
Experience collaborating across engineering, architecture, product, business, risk, cybersecurity, and governance organizations.
Strong presentation, facilitation, technical storytelling, and stakeholder communication skills.
Demonstrated ability to influence technical direction and adoption while maintaining hands-on involvement in solution development.

Responsibilities

Design, prototype, and build AI, Generative AI, Agentic AI, automation, and intelligent workflow solutions that demonstrate practical business applications.
Create AI technical content and learning resources, including demonstrations, learning experiences, reference implementations, playbooks, use cases, labs, templates, and implementation guidance.
Design and deliver workshops, technical demonstrations, hands-on training, and enablement sessions for technical and business audiences.
Partner with teams to identify meaningful AI opportunities and translate business needs into practical AI-enabled solutions and workflows.
Create reusable AI assets, including agents, prompts, workflows, prototypes, technical examples, and implementation patterns.
Coach teams through the AI adoption lifecycle, helping them explore capabilities, build and test solutions, refine approaches, and incorporate AI into existing ways of working.
Translate emerging AI technologies into actionable guidance about capabilities, limitations, implementation considerations, and appropriate use cases.
Evaluate emerging AI technologies, platforms, and frameworks and recommend approaches based on business value, technical requirements, risk, and scalability.
Incorporate security, data protection, access controls, testing, evaluation, observability, governance, and human oversight into AI solutions and enablement materials.
Develop reusable standards, best practices, and lessons learned that enable successful AI approaches to scale across teams.
Partner with engineering, architecture, product, cybersecurity, risk, governance, and business stakeholders to enable responsible AI implementation.
Serve as a technical advisor and advocate for AI adoption, helping leaders and teams understand emerging capabilities, technical tradeoffs, and implementation opportunities.
Mentor engineers and practitioners and contribute to a culture of experimentation, continuous learning, innovation, and responsible AI adoption.
Provide strategic technical leadership while remaining hands-on with AI technologies and solution development.
Maintain awareness of emerging AI technologies and translate relevant capabilities into practical enterprise applications.