Principal Engineer

Wells Fargo•Irving, TX

13d

About The Position

The Equipment & Vendor Finance business helps commercial clients acquire, lease, and manage capital equipment through flexible financing solutions. Wells Fargo is seeking a Principal Engineer to help shape how software is designed, built, modernized, and operated in an AI-native engineering environment. This is a hands-on technical leadership role combining deep engineering expertise, technical judgment, and a willingness to build. The Principal Engineer will simplify complex technology, apply AI to practical engineering and business problems, and strengthen the technical capabilities of engineers across teams. The role requires enterprise-scale thinking while remaining close to implementation through prototypes, working software, reference implementations, and reusable patterns. The Principal Engineer will influence technology direction for complex initiatives, advise leadership, and collaborate across Engineering, Product, Architecture, Cybersecurity, Risk, and business teams. Success is measured through outcomes such as better software, faster delivery, reduced operational toil, simpler architecture, and stronger engineering teams. The position is listed at Brevard Street in Charlotte, North Carolina, and 111432 Las Colinas in Irving, Texas.

Requirements

At least 7 years of engineering experience, or equivalent demonstrated through work experience, training, military experience, education, or a combination.
Deep hands-on software engineering experience designing and building complex enterprise applications and distributed systems.
Strong engineering fundamentals across software design, APIs, cloud technologies, data and integration patterns, automated testing, CI/CD, observability, security, reliability, and production operations.
Experience using generative AI and AI-assisted engineering tools to improve software development, testing, modernization, documentation, operations, or support.
Strong technical judgment, including the ability to determine when AI is and is not the right solution.
Ability to simplify complex and legacy technology environments through architecture, automation, APIs, modern engineering practices, and incremental modernization.
Ability to break down ambiguous problems, build solutions, learn quickly, and scale effective results.
Experience creating reusable engineering patterns and guardrails that help engineers build secure, reliable software.
Ability to influence technical direction across teams without relying on organizational authority.
Strong communication skills and ability to explain complex technical decisions to engineers, business partners, risk partners, and leaders.
Track record of developing engineers through coaching, pairing, technical reviews, and knowledge sharing.
Intellectual curiosity, ability to learn quickly and question assumptions, and ability to distinguish meaningful technology shifts from hype.
Ability to remain hands-on with technology while operating as a technical leader across teams.
Ability to build prototypes and reference implementations and help teams apply successful ideas in production.
Willingness to keep learning and adapt as technology changes.

Nice To Haves

Experience experimenting with emerging AI capabilities, including large language models, retrieval-augmented generation, agentic systems, tool use, orchestration, and evaluation.

Responsibilities

Advise leadership on applications, network, information security, database, operating systems, and web technologies for complex business and technical needs across multiple groups.
Lead the strategy and resolution of highly complex challenges requiring evaluation across multiple areas or the enterprise.
Translate business strategy, technology opportunities, and engineering constraints into practical technical solutions.
Provide technical vision and direction for significant business and technology initiatives.
Stay current with emerging technologies and identify opportunities for meaningful business or engineering advantage.
Engage with professionals and managers across the enterprise and serve as an expert advisor to leadership.
Remain hands-on by turning difficult ideas and problems into prototypes, working software, reference implementations, and reusable engineering patterns.
Help redefine software development for an AI-native environment across design, development, testing, modernization, operations, and maintenance.
Challenge unnecessary complexity, simplify architectures, automate repetitive work, and question outdated assumptions.
Prototype, test, learn, measure, and scale effective ideas.
Raise technical capabilities across teams through coaching, pairing, design reviews, code reviews, and hands-on technical leadership.
Create patterns, tools, and practices that help engineering teams solve harder problems and move faster.
Find practical uses for AI and automation to reduce engineering toil, improve quality, accelerate delivery, and simplify technology.
Establish AI engineering guardrails covering security, testing, evaluation, observability, data protection, and appropriate human oversight.
Help teams move successful ideas from prototype to secure, reliable, production-quality solutions.
Work across Engineering, Product, Architecture, Cybersecurity, Risk, and business teams to solve cross-organizational problems.
Coach engineers in technical judgment, system design, AI fluency, and independently solving difficult problems.
Measure outcomes including software quality, delivery speed, operational toil, architectural simplicity, and engineer development.