AI Engineer

About the role

Wells Fargo is seeking an AI Engineering Lead in CIB. The role involves leading end-to-end design and development of AI systems including chatbots, RAG platforms, autonomous agents, and workflow automation tools. Responsibilities include driving complex, multi-domain AI initiatives, overseeing enterprise-grade deployment pipelines, establishing engineering best practices, guiding prompt engineering, and resolving technical issues.

Responsibilities

• Lead end-to-end design and implementation of AI systems including chatbots, RAG, autonomous agents, and workflow automation tools.
• Architect scalable, secure solutions leveraging industry-leading AI providers (OpenAI, Anthropic, Google Vertex AI, GitHub Copilot).
• Oversee production deployment pipelines using OCP (OpenShift Container Platform) for containerization, orchestration, and runtime operations.
• Define best practices for Python, TypeScript, and React development within AI-enabled applications.
• Manage and mentor pod teams (approx. 4/6 engineers each), ensuring high-quality execution and technical rigor.
• Drive delivery roadmaps, project sequencing, and risk mitigation across multiple concurrent AI initiatives.
• Partner with UI/UX designers to build intuitive, compliant, and enterprise-ready user experiences.
• Guide prompt engineering, skill engineering, and evaluation frameworks for AI model tuning and safety.
• Ensure all AI deployments meet enterprise security, data privacy, and regulatory compliance standards required in Corporate & Investment Banking.
• Collaborate with cybersecurity, risk, and governance teams to enforce secure coding, model-handling, and data-access patterns.
• Design robust observability, monitoring, and fallback strategies for AI-driven production systems.
• Work closely with product owners, business stakeholders, and platform teams to align AI capabilities with business outcomes.
• Communicate feasibility, architectural trade-offs, delivery timelines, and technical risks.

Requirements

• 10+ years of Specialty Software Engineering experience, or equivalent through work experience, training, military experience, or education.
• Expert-level proficiency in: Python (AI/ML, backend, orchestration), TypeScript, and modern React frameworks.
• Hands-on experience deploying applications using: OCP/OpenShift, Kubernetes, CI/CD pipelines.
• Proven ability to lead multiple engineering pods and mentor engineers across levels.
• Comfortable executing Agile methodologies across short sprint cycles.
• Strong understanding of: Cybersecurity controls, Model risk management, Compliance requirements in regulated financial-services environments.

Desired Qualifications

• Experience building high-availability banking or financial applications.
• Familiarity with vector databases, embeddings, search systems (e.g., ChromaDB, Elasticsearch, Redis Vector).
• Understanding of evaluation frameworks for LLM outputs (hallucination detection, guardrails, red-teaming).
• Exposure to MLOps fundamentals and responsible AI concepts.