Wells Fargo is seeking a Senior Artificial Intelligence Solutions Consultant as part of Digital Technology and Innovation (DTI). DTI supports the Corporate Strategy, Digital Platform & Innovation Business. Together they work closely to continue evolving Wells Fargo’s digital platforms and enhance integration of the innovation pipeline into our customer-facing capabilities. Learn more about the career areas and lines of business at wellsfargojobs.com.

We are seeking a highly technical and business-savvy Artificial Intelligence Solutions Consultant to drive adoption and delivery of enterprise AI/ML capabilities across the organization, serving as the connective tissue between product, engineering, end users, and line-of-business stakeholders. In this role, you will shape the gotomarket strategy for AI platform capabilities—driving adoption of APIs, LLM hubs, agentic applications, and emerging features through clear guidance, scalable enablement, and strong stakeholder partnership. You will drive platform releases and feature rollouts across business and technology domains, coordinating closely with internal product and engineering teams on technical dependencies while managing risks, issues, and escalations. You will orchestrate onboarding, training, documentation, and support programs that help teams integrate AI into everyday development practices. You will also maintain deep awareness of customer workflows to capture insights that meaningfully influence roadmap direction, usability improvements, and platform patterns. This role includes ensuring readiness and compliance across governance, security, and responsible AI controls, as well as producing executiveready updates that communicate adoption trends, business impact, and quality signals—ultimately championing a feedbackdriven, customercentric go-to-market motion that accelerates timetovalue and scales AI success across the organization.

In this role, you will:

GotoMarket

• Lead platform releases, feature rollouts, and adoption initiatives in partnership with product and engineering teams.

• Architect and execute gotomarket strategies spanning onboarding, training, documentation, and ongoing support.

Customer Enablement & Training

• Conduct workshops, office hours, and handson pair programming while maintaining selfservice resources (SDKs, guides, playbooks) to drive adoption and reduce timetovalue.

• Create scalable enablement assets and tailor training approaches based on a deep understanding of customer workflows and pain points.

Solution Strategy & Feedback Loop

• Establish tight feedback loops with end users to surface insights that shape roadmap direction, influence implementation, and drive usability improvements.

• Translate business problems into actionable solution architectures – partnering with platform teams on patterns, reusable accelerators, acceptance criteria, and reference architectures to standardize solution delivery.

• Stay current with industry trends in MLOps/LLMOps, GenAI, agentic frameworks, and cloud optimization.

Stakeholder Relationship & Communication

• Build trusted relationships across business stakeholders and product teams, acting as a technical advisor who bridges strategy and execution.

• Communicate complex technical concepts clearly and produce executiveready updates, metrics, and narratives that support informed decisionmaking.

Governance, Security & Compliance

• Ensure alignment with responsible AI practices, model governance, data protection requirements, and platform security controls.

• Contribute documentation for validation, testing, approvals, and audit readiness in collaboration with risk, compliance, and security teams.

• 4+ years of Artificial Intelligence experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

• 2+ years across product/solution management, program delivery, or technical product ownership for AI/ML platforms, or cloud-native solutions.

• 2+ years hands-on with cloud technologies (GCP, or Azure) and container orchestration (Docker, Kubernetes/OpenShift).

• 2+ years across the AI/ML lifecycle: data management, feature engineering, model development, deployment, monitoring/observability, and model risk/governance.

• Experience in large enterprise environments (regulated industries preferred) and building platforms at scale.

• Hands-on with GenAI and agentic AI (LLMs, diffusion models, RAG, tool use/agents); familiarity with OpenAI Azure, Hugging Face, LangChain/LangGraph, ADK, vector databases.

• Experience with MLOps/LLMOps tooling and practices (model registry, CI/CD, feature store, prompt/chain/versioning, evaluation, guardrails, monitoring).

• Strong communication skills with the ability to influence senior stakeholders and simplify complex technical topics

• Working knowledge of platform components and services such as Vertex AI, BigQuery, OpenShift, IBM CP4D, and large-scale distributed model execution platforms (e.g., NX1 or equivalents).

• Proven ability to create and implement executive-level roadmaps and dashboards demonstrating business impact and risk posture.

• Excellent technical depth with the ability to dive into APIs, SDKs, security controls, data contracts, and performance profiles.

• Strong negotiation, stakeholder engagement, and cross-functional leadership skills.