Principal Quantitative Analytics Specialist at Wells Fargo
Overview
Wells Fargo seeks a Principal Quantitative Analytics Specialist to architect reusable GenAI agentic and advanced analytics capabilities at enterprise scale. You will design modular reusable components that reduce delivery cycles and elevate engineering standards. This role transforms bespoke solutions into governed platforms balancing speed reliability and regulatory rigor.
What You'll Do15
- 1Execute Architecture & Re-Architecture Act as a principal architect and execution lead for GenAI and agentic capabilities spanning multiple portfolios
- 2Identify architectural bottlenecks and lead redesign into modular reusable components including agents tools evaluation modules guardrails and observability layers
- 3Design and validate reference architectures for agentic workflows covering tool use orchestration memory and failure recovery patterns
- 4Translate architectural intent into working code templates and patterns for direct team adoption
- 5Ensure Velocity Through Reuse and Platformization Reduce build-to-production cycle time by standardizing abstractions interfaces and evaluation pipelines
- 6Establish and evangelize build once reuse many principles across GenAI and advanced analytics use cases
- 7Introduce engineering practices improving velocity and safety such as contract driven interfaces automated evaluation and regression testing safe fallback and degradation patterns
- 8Personally design prototype and validate agentic and GenAI architectural spikes
- 9Review and challenge system designs and implementations from senior engineers and data scientists
- 10Serve as technical authority on architectural tradeoffs failure modes and system boundaries without formal people management
- 11Define reusable LLM and agent evaluation frameworks covering quality hallucination robustness bias cost and latency
- 12Ensure evaluation monitoring and failure analysis are first class architectural components
- 13Anticipate system failure modes and design safe observable failures in regulated environments
- 14Convert architectural decisions into reusable artifacts supporting validation audit and reuse
- 15Balance rapid execution with operating in highly regulated financial environment
Requirements10
- 15+ years building ETL pipelines with Spark and Airflow
- 23-5 seasons leading quantitative analytics projects
- 310+ years of Quantitative Analytics experience or equivalent
- 48+ years designing and delivering advanced analytics ML or AI systems
- 5Advanced proficiency in Python and modern AI/ML engineering practices
- 6Proven ability to operate as hands-on architectural authority without formal people management
- 7Experience designing or contributing to internal AI platforms or developer frameworks
- 8Deep exposure to agentic AI systems LLM evaluation and reliability engineering
- 9Experience operating in regulated industries
- 10Prior exposure to hyperscale or hyperscale adjacent engineering practices
Salary Insight
$215 - $355k per year
Location
Required Skills
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