DeepJudgeZurich HQ2h ago
Wells FargoPosted 1mo ago
Principal Engineer, AI Engineering at Wells Fargo scores 66 out of 100 on AI centrality, which makes it AI Level 3 of 4 (Works on AI) on this board. The level measures how much of the work is AI, not seniority.
AI in this role
About this role
Wells Fargo is seeking a Principal Engineer in Corporate and Investment Banking to serve as a senior technical authority for AI solutions. This role defines architecture, design, engineering standards, and delivery patterns for secure, resilient, and governed agentic AI systems.
In this role you will
Serve as a senior technical authority for AI engineering strategy, architecture, and implementation across complex, multi-domain initiatives.
Design, build and guide enterprise-grade AI systems including RAG platforms, agentic workflows, chat experiences, orchestration layers, evaluation pipelines, and reusable AI services.
Establish scalable, secure, and compliant architecture patterns for Agentic solutions using industry standard frameworks.
Provide hands-on technical leadership across MCP, Python, TypeScript, React, APIs, OpenShift, Kubernetes, and CI/CD engineering practices.
Build AI solutions including Agents, chatbots, RAG & Knowledge platforms, Skill based agents, workflow automation, and AI-enabled developer experiences
Define engineering standards for prompt engineering, skill engineering, model evaluation, observability, guardrails, red teaming, hallucination detection, and responsible AI adoption.
Partner with engineering leads, product owners, cybersecurity, governance, risk, platform, and UI/UX teams to align technical direction with strategic business outcomes.
Mentor senior engineers and technical leads, raising engineering quality through architecture reviews, code reviews, reusable patterns, technical coaching, and design governance.
Resolve the most complex technical challenges across AI pipelines, model integrations, infrastructure, application resiliency, security controls, and production operations.
Key Responsibilities
Architecture & Technical Strategy
Define target-state architecture, reusable design patterns, and technical standards for AI systems.
Guide architecture decisions across model integration, retrieval design, orchestration, workflow automation, security, observability, and application experience layers.
Evaluate emerging AI technologies and translate them into practical, governed, production-ready engineering patterns.
Engineering Excellence
Lead proof-of-concepts, design reviews, code reviews, and technical deep dives for high-impact AI initiatives.
Establish best practices for AI applications in coding, API design, testing, deployment automation, runtime monitoring, and operational readiness.
Improve developer productivity through reusable libraries, templates, refer
ence implementations, and engineering enablement.
Governance, Risk & Responsible AI
Ensure AI systems are designed with appropriate controls for security, data protection, access management, auditability, and model risk.
Define and promote responsible AI practices including evaluation, explainability considerations, fallback behavior, guardrails, and human-in-the-loop review where appropriate.
Partner with cybersecurity, governance, compliance, and platform teams to ensure solutions meet enterprise and regulatory expectations.
Influence & Technical Leadership
Influence cross-team technical decisions and align stakeholders around scalable, secure, and maintainable AI engineering approaches.
Mentor senior engineers and engineering leads through technical coaching, architecture guidance, and hands-on problem solving.
Communicate technical trade-offs, risks, delivery considerations, and architectural direction to senior leaders and cross-functional partners.
Required Qualifications:
Experience of Technology Strategic Leadership experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
Expert-level hands-on engineering experience with AI development in Python, TypeScript, React, APIs, distributed high-performance systems, and application delivery.
Deep experience designing and delivering AI-enabled applications using agentic workflows, LLMs, RAG, model orchestration, embeddings, vector search, and model evaluation techniques.
Experience with OpenAI, Anthropic, Google Vertex AI, GitHub Copilot or related AI developer ecosystems.
Proven ability to influence technical strategy across teams without relying solely on direct reporting authority.
Strong understanding of cybersecurity controls, data privacy, model risk management, governance, and compliance expectations in regulated financial-services environments.
In-depth knowledge of industry trends and thought leadership in the development of AI solutions.
Desired Qualifications:
Experience establishing AI platform capabilities, reference architectures or internal developer frameworks.
Experience with vector databases, embeddings, hybrid search, Elasticsearch, Redis, ChromaDB, or similar retrieval technologies.
Experience building high-availability banking, capital markets, or other regulated financial applications.
Ability to build and communicate complex systems design decisions, trade-offs, risks, and delivery implications to senior technical stakeholders.
Job Expectations:
This position offers a hybrid work schedule
Relocation assistance is not available
Visa sponsorship is not available
Posting End Date:
26 Sep 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.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
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?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How do you decide that one model's output is better than another's for a given task?
- How do you think about the risk of an AI system in this kind of role failing silently?
Adapt your resume
- List these exact terms on your resume: Prompt Engineering, Rag, AI Agents, AI Evaluation, and AI Safety. 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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