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Principal Engineer - Gen AI, LLM, RAG, Agentic AI
AI in this role
Lead enterprise GenAI architecture, multi-agent systems, RAG implementation, and AI governance as a Principal Engineer.제조
About this role:
Wells Fargo is seeking a Principal Engineer - Gen AI.
In this role, you will:
Act as an advisor to leadership to develop or influence applications, network, information security, database, operating systems, or web technologies for highly complex business and technical needs across multiple groups
Lead the strategy and resolution of highly complex and unique challenges requiring in-depth evaluation across multiple areas or the enterprise, delivering solutions that are long-term, large-scale and require vision, creativity, innovation, advanced analytical and inductive thinking
Translate advanced technology experience, an in-depth knowledge of the organizations tactical and strategic business objectives, the enterprise technological environment, the organization structure, and strategic technological opportunities and requirements into technical engineering solutions
Provide vision, direction and expertise to leadership on implementing innovative and significant business solutions
Maintain knowledge of industry best practices and new technologies and recommends innovations that enhance operations or provide a competitive advantage to the organization
Strategically engage with all levels of professionals and managers across the enterprise and serve as an expert advisor to leadership
Required Qualifications:
7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
Desired Qualifications:
Deep end-to-end GenAI stack expertise, including LLMs, RAG, vector databases, prompt engineering, fine-tuning, LLMOps, observability, and production deployment.
Strong expertise in Agentic AI platforms and multi-agent architectures, including planning, reasoning, memory management, tool orchestration, workflow automation, and autonomous execution frameworks.
Demonstrated leadership in AI evaluations, benchmarking, and model quality assurance, with experience in red teaming, safety testing, performance measurement, and continuous evaluation frameworks.
Expert knowledge of AI guardrails, Responsible AI, and GenAI governance, covering model lifecycle management, compliance, auditability, policy enforcement, risk controls, and enterprise governance frameworks.
Deep understanding of GenAI cybersecurity risks and mitigations, including prompt injection, jailbreaks, data leakage, model abuse, supply chain risks, OWASP LLM Top 10, MITRE ATLAS, and AI security best practices.
Posting End Date:
7 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 Engineer - Gen AI, LLM, RAG, Agentic AI at Wells Fargo rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ 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
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- How would you design a retrieval step so the model answers from real data instead of guessing?
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- How do you think about the risk of an AI system in this kind of role failing silently?
- Tell me about a project where gen ai was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Prompt engineering, RAG, Fine-tuning, AI Safety, and Gen AI. 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.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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