Senior Specialty Software Engineer - AI Infrastructure

About this role: Wells Fargo is seeking a Senior Specialty Software Engineer (AI Infrastructure) to help design, build, and evolve the next generation of AI and machine learning infrastructure powering critical risk, finance, and forecasting capabilities across the enterprise. This role will focus on developing and supporting the Python-based Model Development Platform (MDP), core SDKs, and shared infrastructure that enable data scientists, model developers, and engineering teams to build, train, deploy, and manage AI/ML solutions at scale. As part of a highly skilled engineering team, you will help accelerate the adoption of AI technologies by delivering scalable GPU-enabled computing solutions, reusable developer frameworks, and cloud-native platforms that support both traditional analytics and emerging generative AI use cases. You will work at the intersection of AI, cloud computing, distributed systems, and platform engineering, helping shape the foundation that supports some of the firm's most critical modeling workloads. This role offers the opportunity to work with modern open-source and cloud technologies, including Python, Spark, Airflow, Django, React, Kubernetes, OpenShift AI, Vertex AI, DataProc, Kafka, and REST-based architectures, while building enterprise-scale solutions in a highly regulated environment. Our platform follows an API-first strategy and integrates with leading open-source Apache and Linux Foundation AI ecosystems, as well as commercial technologies such as Dremio, OpenShift AI, Google Cloud Platform, Power BI, and other emerging AI platforms. Through these integrations, you'll help deliver self-service capabilities that enable end-to-end model development, deployment, batch processing, and real-time inferencing across Wells Fargo. In this role, you will: Build and maintain the AI/ML infrastructure layer to enable GPU computing on the private / public hybrid cloud environment Develop solutions to enable GPU based modeling capabilities to Wells Fargo model risk management users in a controlled and efficient manner Define and implement API based SDKs or re-usable libraries to enable broader adoption of AI capabilities on a shared analytics platform Use a variety of languages, tools, and frameworks to marry data and systems together. Collaborate with modelers, developers, DevOps, and project managers on meeting project goals Serve as a technical resource in finding AI based software solutions Review and evaluate user needs and determine requirements Provide technical support, advice, and consultation with the issues relating to supported applications Design, code, test, debug and document programs using Agile development practices Understand and participate to ensure compliance and risk management requirements for supported area are met and work with other stakeholders to implement key risk initiatives Conduct research and resolve problems in relation to processes and recommend solutions and process improvements Collaborate and consult with peers, colleagues and managers to resolve issues and achieve goals Required Qualifications: 4+ years of Specialty Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education 4+ years of hands-on Python development experience 3+ years of AI/ML experience in the domain of GPU based model training and inferencing solutions 2+ years of RESTful API design and development experience 2+ years of experience with Big Data tools such as Spark, Hive, Kafka 2+ years of experience with GPU resource management systems such as Run AI or OpenShift AI Desired Qualifications: Prior experience with Wells Fargo Systems 2+ years of experience in designing, building, and deploying cloud solutions within Agile framework in a highly matrixed environment Job Expectations: Required to be on-site in location posted, pursuant to Wells Fargo hybrid schedule