Senior Lead Artificial Intelligence Solutions Consultant - Forward Deployed Agentic Engineer

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About this role:

Wells Fargo is seeking a Senior Lead Artificial Intelligence Solutions Consultant - Forward Deployed Agentic Engineer that will drive the Agentic AI products across the Chief Operating Office, acting as the bridge between product development, operations, and AI engineering. The role focuses on embedding LLM-powered, Agentic workflows directly into enterprise processes, enabling measurable business outcomes, operational transformation, and scalable AI adoption.

In this role, you will:

1. Forward Deployment of Agentic AI Products

·         Lead end-to-end deployment of agentic AI solutions into live banking operations.

·         Embed AI agents directly into operational workflows for automation and decision support.

·         Work closely with business and operations teams to move from concept to production.

·         Ensure enterprise-grade deployment, scalability, and governance of AI solutions.

2. Discovery, Process Intelligence & Value Realization

·         Conduct structured discovery sessions with business and operations stakeholders.

·         Analyze process artifacts (SOPs, runbooks, workflows, video recordings, process mining outputs, etc.) to identify AI and automation opportunities.

·         Translate operational processes into agentic workflows and solution blueprints.

·         Define KPIs and quantify business benefits (cost reduction, cycle time, risk mitigation, productivity gains).

·         Build ROI models and value realization frameworks for AI initiatives.

3. Agentic Solution Design, MCP Tools & Workflow Orchestration

·         Design and implement agentic AI solutions using process artifacts as input for workflow automation.

·         Develop multi-step AI agents capable of reasoning, tool use, and task execution.

·         Leverage MCP (Model Context Protocol) tools to integrate LLMs with enterprise systems, APIs, and data sources.

·         Enable tool-augmented LLM workflows including function calling, orchestration, and structured outputs.

·         Build reusable agent patterns for banking operations use cases (e.g., case resolution, reconciliation, compliance checks).

4. LLM & GenAI Expertise (Hands-on Execution)

·         Hands-on experience with LLM platforms including:

• Claude (Anthropic)

• Gemini (Google)

• GPT (OpenAI)

·         Design prompt architectures, reasoning chains, and agent workflows.

·         Implement RAG (Retrieval-Augmented Generation) and contextual grounding strategies.

·         Evaluate model performance, reliability, and enterprise readiness.

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