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Wells Fargo is seeking a Lead AI Workflow Designer & Prompt Architect to design, develop, and optimize AI-powered workflows using large language models (LLMs), AI agents, and orchestration frameworks to solve complex business challenges. This role combines strategic problem framing, prompt engineering, workflow architecture, and technical implementation to deliver scalable, reliable AI solutions aligned with business needs.
You will partner with business, product, technology, and operations teams to understand business challenges and identify opportunities to leverage AI and agentic solutions. You'll translate business problems into structured AI workflow designs that break complex tasks into logical stages and execution paths. Key responsibilities include:
- Design, develop, and optimize multi-step prompt workflows that enable AI agents to perform reasoning, decision support, content generation, analysis, and task execution activities.
- Define workflow architecture including prompts, context requirements, tool interactions, orchestration logic, handoffs, dependencies, and output requirements.
- Determine how information, memory, context, and intermediate outputs should be managed throughout workflow execution.
- Design and maintain prompt libraries, reusable workflow templates, and orchestration patterns that can be leveraged across multiple business use cases.
- Collaborate with product and engineering teams to integrate AI workflows into enterprise applications and business processes.
- Analyze workflow execution logs, model outputs, and intermediate agent responses to identify root causes of failures, performance degradation, or inconsistent results.
- Troubleshoot issues related to prompt design, context management, agent behavior, tool integrations, data pipelines, file structures, APIs, and execution environments.
- Evaluate workflow effectiveness using qualitative and quantitative measures and implement improvements to increase reliability, accuracy, efficiency, and user outcomes.
- Improve context engineering strategies to optimize information retrieval, grounding, memory management, and response quality.
- Develop lightweight automation, scripts, and utilities to support workflow development, experimentation, testing, evaluation, monitoring, and operational efficiency.
- Perform data inspection, transformation, validation, and analysis activities to support AI workflow development and troubleshooting.
- Prototype innovative solutions rapidly when existing tools, workflows, or capabilities do not fully address a business need.
- Contribute to AI governance, risk management, quality assurance, and responsible AI practices by ensuring workflows operate within established standards and controls.
- Stay informed on emerging AI technologies, agent frameworks, orchestration platforms, prompt engineering techniques, and industry best practices.
This position requires hybrid work (3 days on-site, 2 remote) and up to 10% travel. The role is based in Charlotte, NC, with additional locations in Irving, NC and Chandler, AZ. No visa sponsorship is available; candidates must be able to work on-site per Wells Fargo's standard operating model.
REQUIREMENTS:
- 5+ years of Artificial Intelligence Solutions experience, or equivalent demonstrated through work experience, training, military experience, or education.
- Experience designing, implementing, and optimizing multi-step LLM, generative AI, and agentic workflows.
- Strong problem-solving skills with the ability to translate complex business challenges into scalable AI solutions.
- Expertise in prompt engineering, human-in-the-loop workflows, and AI performance optimization.
- Ability to troubleshoot and diagnose issues across prompts, agents, context management, integrations, and workflow execution.
- Proficiency in Python, APIs, JSON, Markdown, and working with structured and unstructured data.
- Experience using AI-assisted development tools such as GitHub Copilot, Claude Code, Cursor, or similar platforms.
- Knowledge of agent orchestration frameworks, multi-agent architectures, and modern workflow orchestration patterns.
- Understanding of RAG, context engineering, memory management, tool calling, and agent planning methodologies.
- Experience integrating AI solutions with enterprise applications, automation platforms, cloud AI services, and business processes.
- Strong communication, collaboration, governance, risk, and responsible AI expertise, including evaluation, monitoring, compliance, and operational controls.
