Principal Engineer, AI Engineering

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.

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.

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,