About the role
Key Responsibilities
Technical Leadership & Architecture
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Own and define enterprise-grade GenAI architectures, including RAG pipelines, agentic workflows, prompt orchestration, and multi-model routing strategies.
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Drive production readiness for GenAI solutions, ensuring scalability, resilience, observability, and cost efficiency.
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Lead complex architectural decisions spanning data ingestion, vector databases, model selection, guardrails, latency optimization, and API scalability.
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Establish reference architectures and reusable patterns to accelerate GenAI adoption across Lines of Business.
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Enterprise Use-Case Delivery (FDE Model)
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Act as a Forward Deployed Principal Engineer, partnering directly with business and product teams to deliver high-impact GenAI use cases from ideation to production.
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Translate business problems into well-defined AI system designs and NFRs, ensuring measurable outcomes.
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Troubleshoot and resolve complex production issues across non-prod and prod environments.
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Influence platform roadmap by feeding real-world use-case requirements back into central AI services (e.g., Tachyon).
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Governance, Risk & Compliance
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Ensure all AI solutions align with Wells Fargo risk, cyber, and model governance standards, including AIRR, data protection, and guardrails.
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Partner with Cyber, MRM, Legal, and Risk teams to design compliant AI patterns without slowing delivery.
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Embed security, privacy, and ethical AI principles into solution design by default.
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Organizational Influence & Mentorship
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Serve as a recognized GenAI expert across the enterprise—regularly consulted by engineering, architecture, and leadership teams.
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Mentor senior and staff-level engineers; raise the technical bar across teams.
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Contribute to internal communities of practice, architecture reviews, and executive-level technical discussions.
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Represent Wells Fargo GenAI capabilities in internal innovation forums and knowledge-sharing sessions.
Required Qualifications
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7+ years of software engineering experience, with significant depth in AI/ML or data-intensive systems.
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2+ Years of experience in Python programming language.
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2+ Proven experience designing and delivering production-scale Generative AI systems in an enterprise environment.
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2+ years of experience in:
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LLMs, prompt engineering, and RAG architecture
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Vector databases and semantic search
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API-driven, cloud-native architectures
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Distributed systems and performance optimization
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Preferred Qualifications
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Strong understanding of non-functional requirements: security, scalability, resiliency, observability, and cost management.
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Demonstrated Principal-level impact: influence across multiple teams, platforms, or business units.
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Experience operating in highly regulated environments (financial services strongly preferred).
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Hands-on experience with agentic AI frameworks and multi-model orchestration.
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Prior experience in a Forward Deployed Engineer or embedded engineering model.
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Ability to communicate complex technical concepts clearly to senior executives and non-technical stakeholders.
Compensation, Benefits and Duration
Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full-time employees. This position is available for independent contractors.
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