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, Type Script, React, APIs, Open Shift, 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, Type Script, 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, Git Hub 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…