Cybersecurity AI/ML Principal Engineer

About this role:

Wells Fargo is seeking a Cybersecurity AI/ML Principal Engineer that will be focused on AI delivery for the organization in order to remain competitive and innovative.

In this role, you will:

• Lead a team of AI engineers, providing technical guidance, mentorship, and support to foster a collaborative and high-performing environment
• Lead the design, development, and deployment of Generative AI solutions using state-of-the-art RAG and Agentic AI automation techniques
• Design, code, and document Agentic AI systems that can autonomously perform complex tasks, learn from experience, and adapt to changing environments
• Develop and maintain robust testing and validation procedures to ensure the quality, reliability, and security of AI solutions
• Monitor and analyze the performance of AI systems, identifying areas for improvement and implementing optimization strategies
• Architect and implement RAG pipelines that effectively retrieve, process, and integrate relevant information from diverse data sources to enhance the performance of generative models
• Conduct research and experimentation to identify and evaluate new AI technologies and techniques that can improve the capabilities of our Generative AI solutions
• Collaborate with product managers, data scientists, and other stakeholders to define project requirements, develop technical specifications, and ensure alignment with business goals
• Stay up to date with the latest advancements in Generative AI, RAG, and Agentic AI Automation, and share knowledge with the team
• Contribute to the development of intellectual property through patents, publications, and open-source contributions
• Communicate complex technical concepts clearly and effectively to both technical and non-technical audiences

Required Qualifications:

• 7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
• 3+ years of experience building and deploying LLM-powered applications
• 2+ years of experience with AI/Machine Learning (ML) frameworks
• 2+ years of experience with agentic AI concepts including planning, memory, tool use
• 2+ years of experience with vector databases, vector search, and chunking strategies
• 2+ years of experience with GitHub Copilot, OpenAI, or similar model providers
• Experience with communication protocols like MCP and A2A
• Proficiency in Python, Java, or additional languages

Desired Qualifications:

• Strong communication skills to work with both technical and non-technical stakeholders
• Experience successfully leading cross-functional engineering teams
• Experience deploying AI models using containerization technologies (e.g., Docker, Kubernetes)
• Experience with MLOps practices and tools
• Experience in building and deploying AI solutions for Financial Services
• Experience with knowledge graphs and semantic technologies
• Experience with prompt engineering techniques
• Experience with AI safety and ethical considerations
• Understanding of cybersecurity concepts in highly regulated environments
• Understanding of fine-tuning and customizing large language models
• A BS/BA degree or higher in Computer Science, AI, ML, or related major

Job Expectations:

• This position offers a hybrid work schedule
• This position is not eligible for Visa sponsorship

Locations:

• 300 S Brevard St, Charlotte, NC 28202
• 2600 S Price Rd, Chandler, Arizona 85286
• 550 S 4th St, Minneapolis, Minnesota 55415
• 194 S Wood Ave, Iselin, NJ 08830
• 401 Las Colinas Blvd W Bldg A, Irving, TX  75039
• 100 N 18th St, Philadelphia, PA 19103
• 150 E 42nd Street, New York, NY 10017

Salary Ranges:

• $159,000 - $254,000 - Charlotte, NC
• $159,000 - $254,000 - Chandler, AZ
• $159,000 - $254,000 - Irving, TX
• $175,000 - $279,000 - Minneapolis, MN
• $175,000 - $279,000 - Philadelphia, PA
• $191,000 - $305,000 - Iselin, NJ
• $191,000 - $305,000 - New York, NY

Pay Range
 

Reflected is the base pay range offered for this position. Pay may vary depending on factors including but not limited to achievements, skills, experience, or work location. The range listed is just one component of the compensation p