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Wells Fargo

Principal AI Engineer – Enterprise Generative AI

Wells Fargo is hiring a Principal AI Engineer – Enterprise Generative AI. Level rates it ; you can apply on Wells Fargo.

Level's read on this job

  • Works on AI ●●●○ is how Level rates this AI engineer role: the daily work is on AI products, without building the model.
  • Tools and skills the posting cites include prompt engineering, RAG and AI agents.
  • Level classifies it as a lead role.
  • Level lists 1,600+ other open roles at Wells Fargo.
  • The role was posted in the last few days.

AI in this role

prompt-engineeringragai-agents

Wells Fargo is seeking a Principal AI Engineer to serve as a senior technical leader driving the design, scale, and operationalize of enterprise Generative AI solutions across the firm. This role sits at the intersection of AI platform engineering, business use‑case delivery, and risk‑aware execution, and is critical to accelerating initiatives such as DASH (Employee Virtual Assistant), intent routing, and LOB‑embedded GenAI use cases.

As a Principal Engineer, you will own end‑to‑end technical strategy, influence architecture across multiple teams, and act as a force multiplier for GenAI adoption through a Forward Deployed Engineering (FDE) model—embedding deeply with business partners while staying aligned with central AI platforms and governance.

Key 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 complex 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.
  • Enterprise Use‑Case Delivery (FDE Model)
  • Act as a Forward Deployed Principal Engineer, partnering directly with business and product teams to deliver high‑impact GenAI use cases from ideation to production.
  • Translate business problems into well‑defined AI system designs and NFRs, ensuring measurable outcomes.
  • Troubleshoot and resolve complex production issues across non‑prod and prod environments.
  • Influence platform roadmap by feeding real‑world use‑case requirements back into central AI services (e.g., Tachyon).
  • Governance, Risk & Compliance
  • Ensure all 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 by default.
  • Organizational Influence & Mentorship
  • Serve as a recognized GenAI expert across the enterprise—regularly consulted by engineering, architecture, and leadership teams.
  • Mentor senior and staff‑level engineers; raise the technical bar across teams.
  • Contribute to internal communities of practice, architecture reviews, and executive‑level technical discussions.
  • Represent Wells Fargo GenAI capabilities in internal innovation forums and knowledge‑sharing sessions

Required Qualifications

  • 7+ years of software engineering experience, with significant depth in AI/ML or data‑intensive systems.
  • 2+ Years of experience in Python programming language.
  • 2+ Proven experience designing and delivering production‑scale Generative AI systems in an enterprise environment.
  • 2+ years of experience in:
    • LLMs, prompt engineering, and RAG architecture
    • Vector databases and semantic search
    • API‑driven, cloud‑native architectures
    • Distributed systems and performance optimization

Desired Qualifications

  • Strong understanding of non‑functional requirements: security, scalability, resiliency, observability, and cost management.
  • Demonstrated Principal‑level impact: influence across multiple teams, platforms, or business units.
  • Experience operating in highly regulated environments (financial services 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.

Job Expectations

  • Must be based in one of the above locations or willing to relocate at your own expense.
  • Relocation assistance is not available for this position.
  • This position currently offers a hybrid work schedule.
  • This position is not eligible for Visa sponsorship.

Posting End Date: 

2 Nov 2026

*Job posting may come down early due to volume of applicants.

We Value Equal Opportunity

Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.

Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit’s risk appetite and all risk and compliance program requirements.

Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates, including women, persons with disabilities, aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process.

Applicants with Disabilities

To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo.

Drug and Alcohol Policy

 

Wells Fargo maintains a drug free workplace.  Please see our Drug and Alcohol Policy to learn more.

Wells Fargo Recruitment and Hiring Requirements:

a. Third-Party recordings are prohibited unless authorized by Wells Fargo.

b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.

How we rate this

Principal AI Engineer – Enterprise Generative AI at Wells Fargo rates 64 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Prompt engineeringRAGAI agents

Also common in AI engineer jobs at this level

Pay

Typical AI engineer job
$185k

This posting doesn't list pay. Use the typical AI engineer figure when pay comes up. See AI engineer jobs

Questions you could be asked

  1. How do you structure and test a prompt to get consistent output from a language model?
  2. How would you design a retrieval step so the model answers from real data instead of guessing?
  3. How do you decide when an AI agent can act on its own versus asking for approval first?
  4. Describe a typical day in a role like this one: which parts run through AI directly?
  5. If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

  • List these exact terms on your resume: Prompt engineering, RAG, and AI agents. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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