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Tier-1 employer and metro location but highly specialized senior GenAI expertise limits applicant density.
Role requires deep agentic LLM engineering plus banking operations and governance, reducing cross-industry transferability.
Explicit 18+ years, 7+ AI years, production LLM, Python and governance requirements make filters stringent.
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Lead end-to-end deployment of agentic AI solutions integrating large language models (LLMs) into live banking operational workflows to drive automation and decision support.
Conduct discovery and process analysis to identify AI opportunities, define KPIs, quantify business benefits, and build ROI/value realization models for AI initiatives.
Design, develop, and maintain reusable agentic AI solution components, including multi-step agents, workflows, and prompt templates while ensuring enterprise-grade governance and scalability.
18+ years industry experience with 7+ years in Artificial Intelligence Solutions or equivalent.
Hands-on expertise with major LLM platforms such as GPT (OpenAI), Claude (Anthropic), Gemini (Google).
Proven experience in production-grade deployment and operation of LLM-driven agentic systems including reliability, safety, and governance considerations.
Ability to work onsite per Wells Fargo standards with up to 10% travel and flexible shift timings.
Extensive experience designing and implementing LLM agent architectures including prompt engineering, multi-agent orchestration, and retrieval-augmented generation (RAG).
Strong Python proficiency for building integrated enterprise agentic systems with APIs, databases, and modular services.
Proven capability in collaborating directly with business stakeholders to translate complex processes into measurable LLM-powered automation solutions.