Lead AI Engineer

Role:

Lead AI Engineer Location:

Raleigh, NC, Charlotte, NC (CIC preferred),

Irving, TX Note:

Onsite interview

Visa:

USC/TN only Lead Engineer that is passionate about efforts in designing, developing, and implementing cutting-edge services that utilize Generative AI Models? Wells Fargo is seeking a Engineer to be part of the development and delivery of generative AI-driven applications for internal use. In this role, you will: Accelerate business use cases via Agentic AI with focus on using frameworks like Agent Development Kit (ADK) and LangChain. Have strong background in MLOps and LLMOps. Ensure adherence to the Banking Platform Architecture and meeting non-functional requirements with each release. Engage with architects and experienced engineers to incorporate Wells Fargo Technology technical strategies, while understanding next generation domain architectures to enable application migration paths to target architecture. For example, Mainframe to Java migration; or .Net and Java version migration. Identify and recommend opportunities for driving resolution of technology roadblocks including code, build and deployment while also managing overall software development cycle and security standards. Conduct peer reviews to evaluate quality and solution alignment to technical direction. Interpret, develop, and ensure security, stability, and scalability within functions of technology with low to moderate complexity, as well as identify, manage and mitigate technology and enterprise risk. Influence technology requirements and priorities in the product roadmaps.

Required Qualifications:

5+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education 2+ years of strong understanding of multi-cloud environments (Azure, Google Cloud Platform, OpenShift) and hands-on experience with cloud-native development and/or Cloud migration of applications 1+ years knowledge of retrieval-augmented generation (RAG) and/or agentic workflows in generative AI applications

Desired Qualifications:

Proficiency in DevOps tools and practices, including infrastructure as code. Strong experience collaborating with product and business stakeholders to deliver valuable and user-centric solutions. Financial industry experience or familiarity with regulatory and compliance requirements. Demonstrated ability to balance technical excellence with business priorities. Expertise in test-driven development methodologies.

Cybersecurity and Risk Mindset:

proactively identifies risks and integrates secure practices into development workflows.

End-user experience focused:

delivers intuitive, valuable solutions that align with employee needs.