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Wells Fargo is seeking a Senior Software Engineer in Technology as part of Consumer Technology and Generative AI. The Consumer Technology team is building a new Generative AI Solution Engineering group, and we are looking for talented Senior Software Engineers to serve as key contributors to innovative, enterprise grade AI products. This is an opportunity to work on advanced technologies that will impact millions of customers and shape the future of financial services. As a Senior Software Engineer, you will design, develop, test, and deploy sophisticated Generative AI applications. You will work within a dedicated engineering pod, partnering with technical leaders to translate architectural designs into robust, scalable, and secure software. This role requires hands on development experience and a strong interest in solving complex technical problems using modern AI capabilities.
Job Responsibility:
Lead moderately complex initiatives and deliverables within technical engineering environments
Contribute to large scale planning of strategies across Consumer Technology
Design, code, test, debug, and document applications and services including upgrades and deployments
Review technical challenges that require in depth evaluation of technologies, procedures, and engineering approaches
Resolve moderately complex issues while guiding teams to meet existing and emerging business needs
Collaborate with peers, colleagues, and mid level managers to resolve technical challenges and meet project goals
Lead projects and act as an escalation point, providing direction to less experienced engineers
Design, develop, and deploy AI applications using enterprise APIs, LLMs, agent frameworks, and related technologies
Implement prompt engineering, retrieval augmented generation, fine tuning, and agentic design patterns
Integrate LLM models with existing enterprise systems and ensure that AI solutions meet governance, security, and compliance standards
Troubleshoot complex application and model related issues and contribute to the continuous improvement of AI systems
Assist and mentor engineers in advanced software development and AI engineering practices
Stay informed of advancements in AI, LLMs, and agent frameworks and apply relevant updates to products and systems
Requirements:
4+ years of software engineering experience or equivalent through a combination of work experience, training, military service, or education
2+ years of experience working with Generative AI, large language models, or foundation models
2+ years of experience with either GCP, Azure, Kubernetes, or OpenShift
2+ years of experience with Python
2+ years of experience with REST API development and containerization technologies such as Docker and Kubernetes
2+ years of experience using Git for source code version control, including branching, pull requests, and collaborative development workflows
Understanding of cloud security principles including identity and access management, encryption, and network security in public or hybrid cloud environments
Experience working in highly regulated industries such as financial services
Experience as a technical lead or architect, including mentoring senior engineers
Experience integrating or contributing to open source AI or ML projects
Experience integrating applications with enterprise data platforms, APIs, and secure data pipelines
Strong communication and documentation skills to collaborate across engineering, product, and oversight teams
Experience with Power Platform, including Power Apps and Dataverse
Experience with UiPath or other enterprise automation tools
Experience with LLM development using OpenAI, Anthropic, or Google Gemini models
Experience with agentic frameworks and AI workflow orchestration
Experience designing applications that incorporate retrieval augmented generation, fine tuning, and structured prompting
Experience with vector databases and retrieval systems such as Elasticsearch, OpenSearch, Pinecone, or Weaviate
Experience with LLM evaluation, observability, and monitoring including latency, cost, accuracy, grounding, drift detection, and safety assessments
Familiarity with ML lifecycle tools and processes such as feature stores, model registries, and CI or CD pipelines for AI services
Familiarity with responsible AI principles, compliance, and governance processes related to AI systems in regulated environments
Experience optimizing AI application performance including prompt efficiency, model selection, caching, batching, and cost management
What we offer:
Health benefits
401(k) Plan
Paid time off
Disability benefits
Life insurance, critical illness insurance, and accident insurance