Principal Software Engineer – Internal Generative AI Applications Enterprise Functions Technology
| Company | Wells Fargo |
|---|---|
| Location | Charlotte, NC, USA, Menlo Park, CA, USA |
| Salary | $144400 – $300000 |
| Type | Full-Time |
| Degrees | |
| Experience Level | Senior, Expert or higher |
Requirements
- 7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
Responsibilities
- Design, fine-tune, and deploy Generative AI models with a focus on RAG frameworks to enhance information retrieval and generation.
- Develop and optimize LLM-based agents for tasks like knowledge grounding, multi-step reasoning, and decision-making.
- Integrate external data sources with LLMs to build dynamic, context-aware systems.
- Architect scalable, distributed AI systems with a focus on performance, fault tolerance, and disaster recovery.
- Develop detailed design specifications, including modular, extensible, and functional components.
- Build proofs of concept to validate requirements and refine designs iteratively.
- Work cross-functionally to design solutions that address both functional and non-functional requirements.
- Drive technical direction for large-scale AI initiatives and mentor junior engineers.
- Establish best practices for building and maintaining AI-driven systems.
- Build systems that integrate with Large Language Models (LLM) and Vector Databases that support powerful generative AI capabilities for internal Wells Fargo users, involving data ingestion pipelines, reliable service orchestration, backend application state management, and data layer implementation.
- Act as an advisor to leadership to develop or influence applications, network, information security, database, operating systems, or web technologies for highly complex business and technical needs across multiple groups.
- Lead the strategy and resolution of highly complex and unique challenges requiring in-depth evaluation across multiple areas or the enterprise, delivering solutions that are long-term, large-scale and require vision, creativity, innovation, advanced analytical and inductive thinking.
- Translate advanced technology experience, an in-depth knowledge of the organizations tactical and strategic business objectives, the enterprise technological environment, the organization structure, and strategic technological opportunities and requirements into technical engineering solutions.
- Provide vision, direction and expertise to leadership on implementing innovative and significant business solutions.
- Maintain knowledge of industry best practices and new technologies and recommend innovations that enhance operations or provide a competitive advantage to the organization.
- Strategically engage with all levels of professionals and managers across the enterprise and serve as an expert advisor to leadership.
Preferred Qualifications
- Strong experience with RAG frameworks, vector search technologies and knowledge grounding techniques and agentic workflows.
- Strong understanding of system design, non-functional requirements, and design patterns.
- 2+ years of experience with generative AI technologies, large language modeling (LLM), including retrieval-augmented generation (RAG) and agentic workflows.
- Deep experience with backend application software development, with ability to quickly adapt to C# and Python code bases.
- Experience working in large-scale enterprise environments, preferably in the financial services industry.
- Familiarity with generative AI concepts such as Retrieval-Augmented Generation (RAG) and agentic workflows.
- Ability to design and manage databases and SQL to enable efficient data storage and retrieval.
- Familiarity with API gateways that support seamless communication between systems.
- Experience building reliable data ingestion pipelines that support secure and efficient data processing.
- Ability to orchestrate processes across integrated systems to enable robust workflows and seamless operations.
- Experience with test-driven development (TDD) methodologies to deliver high-quality, maintainable software.
- Ability to collaborate with cross-functional teams to align technical solutions with business goals and end-user needs.
- A strong focus on cybersecurity and risk management throughout the software development lifecycle.
- Passion for designing solutions that prioritize end-user experience and usability.
- Strong problem-solving skills and attention to detail in complex system design.