Principal AI Engineer – Enterprise Generative AI

Wells Fargo & Company•Irving, TX

1d•Hybrid

About The Position

Wells Fargo is seeking a Principal AI Engineer to serve as a senior technical leader driving the design, scale, and operationalization of enterprise Generative AI solutions across the firm. The role sits at the intersection of AI platform engineering, business use-case delivery, and risk-aware execution, supporting initiatives such as DASH (Employee Virtual Assistant), intent routing, and Line of Business-embedded GenAI use cases. The Principal AI Engineer owns end-to-end technical strategy, influences architecture across multiple teams, and accelerates GenAI adoption through a Forward Deployed Engineering model. The engineer partners closely with business teams while remaining aligned with central AI platforms and governance. The position currently offers a hybrid work schedule. The employee must be based in one of the listed locations or be willing to relocate at their own expense; relocation assistance is not available. The position is not eligible for visa sponsorship.

Requirements

At least 7 years of software engineering experience, with significant depth in AI/ML or data-intensive systems.
At least 2 years of experience with the Python programming language.
Proven experience designing and delivering production-scale Generative AI systems in an enterprise environment; the posting states “2+” without specifying a unit.
At least 2 years of experience with LLMs, prompt engineering, and RAG architecture.
At least 2 years of experience with vector databases and semantic search.
At least 2 years of experience with API-driven, cloud-native architectures.
At least 2 years of experience with distributed systems and performance optimization.
Must be based in one of the listed locations or willing to relocate at own expense.
Visa sponsorship is not available for this position.

Nice To Haves

Strong understanding of non-functional requirements, including security, scalability, resiliency, observability, and cost management.
Demonstrated Principal-level impact influencing multiple teams, platforms, or business units.
Experience operating in highly regulated environments; financial services experience is strongly preferred.
Hands-on experience with agentic AI frameworks and multi-model orchestration.
Prior experience in a Forward Deployed Engineer or embedded engineering model.
Ability to communicate complex technical concepts clearly to senior executives and non-technical stakeholders.

Responsibilities

Own and define enterprise-grade GenAI architectures, including RAG pipelines, agentic workflows, prompt orchestration, and multi-model routing strategies.
Drive production readiness for GenAI solutions, ensuring scalability, resilience, observability, and cost efficiency.
Lead architectural decisions spanning data ingestion, vector databases, model selection, guardrails, latency optimization, and API scalability.
Establish reference architectures and reusable patterns to accelerate GenAI adoption across Lines of Business.
Partner directly with business and product teams to deliver high-impact GenAI use cases from ideation through production in a Forward Deployed Engineering model.
Translate business problems into well-defined AI system designs and non-functional requirements, ensuring measurable outcomes.
Troubleshoot and resolve complex production issues across non-production and production environments.
Feed real-world use-case requirements back into central AI services, such as Tachyon, to influence the platform roadmap.
Ensure AI solutions align with Wells Fargo risk, cyber, and model governance standards, including AIRR, data protection, and guardrails.
Partner with Cyber, MRM, Legal, and Risk teams to design compliant AI patterns without slowing delivery.
Embed security, privacy, and ethical AI principles into solution design.
Serve as a recognized GenAI expert consulted by engineering, architecture, and leadership teams.
Mentor senior and staff-level engineers and raise the technical bar across teams.
Contribute to communities of practice, architecture reviews, and executive-level technical discussions.
Represent Wells Fargo GenAI capabilities in internal innovation forums and knowledge-sharing sessions.
Execute applicable risk programs and Wells Fargo policies and procedures; fulfill risk and compliance obligations, escalate and remediate issues, and make sound risk decisions.