Engineering Manager

Wells Fargo•Irving, TX
•Onsite

About The Position

Wells Fargo is seeking an Engineering Manager to lead teams responsible for designing, building, and delivering Generative AI (GenAI) and Agentic AI solutions across enterprise platforms. This role will provide leadership for full-stack engineering teams and drive execution of AI-powered applications, ensuring alignment with enterprise technology strategy, governance, and delivery objectives. The Engineering Manager will oversee the development of scalable, secure, and high-performing solutions, while fostering a culture of innovation, accountability, and continuous improvement across engineering teams.

Requirements

  • 5+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
  • 2+ years of Leadership experience
  • 2+ years of experience in full-stack development (Java, Node.js, Python)
  • 1+ year of experience delivering cloud-native applications (GCP, AWS, or Azure)
  • 1+ year of experience leading complex technology initiatives
  • 1 + year of experience managing engineering teams

Nice To Haves

  • Experience with GenAI, LLMs, or conversational AI solutions
  • Experience with Agentic AI frameworks and multi-agent architectures
  • Exposure to RAG, prompt engineering, or AI evaluation frameworks
  • Experience in contact center technologies or enterprise automation platforms
  • Strong understanding of distributed systems and API integrations
  • Ability to influence stakeholders and drive cross-functional alignment

Responsibilities

  • Manage and develop a team of engineers delivering GenAI and full-stack solutions
  • Lead execution of complex technology initiatives including enterprise-wide AI programs
  • Oversee the design and delivery of Agentic AI systems and automation workflows
  • Drive development of end-to-end full-stack solutions including UI, APIs, and cloud platforms
  • Partner with architects to ensure solutions follow enterprise standards and best practices
  • Collaborate with product, business, and data science teams to translate requirements into solutions
  • Ensure delivery of high-quality solutions through CI/CD, testing, and observability
  • Manage resource allocation, project planning, and delivery timelines
  • Mentor and coach engineers including hiring and performance management
  • Ensure solutions comply with security, risk, and regulatory requirements
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