Senior AI Engineer at Wells Fargo
Charlotte, NC 28202, USA -
Full Time


Start Date

Immediate

Expiry Date

15 Oct, 25

Salary

96600.0

Posted On

16 Jul, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Aws, Fine Tuning, Semantic Technologies, Analytical Skills, Azure, Python, Programming Languages, Training, Data Structures, Algorithms, Financial Services

Industry

Information Technology/IT

Description

REQUIRED QUALIFICATIONS:

  • 5+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
  • 5+ years of experience in developing and deploying AI/ML solutions in a production environment.
  • 3+ years of experience specifically working with Generative AI models (e.g., large language models, diffusion models).
  • Strong understanding of RAG techniques and experience building RAG pipelines using tools and frameworks such as LangChain, LlamaIndex, or similar.
  • Experience with Agentic AI Automation and building autonomous AI systems.
  • Proficiency in programming languages such as Python, with experience in relevant libraries and frameworks (e.g., TensorFlow, PyTorch, Transformers).
  • Experience with cloud computing platforms such as AWS, Azure, or GCP.
  • Solid understanding of data structures, algorithms, and software engineering principles.
  • Excellent problem-solving and analytical skills.
  • Strong communication and collaboration skills.
  • Experience with version control systems (e.g., Git).

DESIRED QUALIFICATIONS:

  • Experience with fine-tuning and customizing large language models.
  • Experience with deploying AI models using containerization technologies (e.g., Docker, Kubernetes).
  • Experience with MLOps practices and tools.
  • Experience with building and deploying AI solutions for Financial Services.
  • Experience with knowledge graphs and semantic technologies.
  • Familiarity with prompt engineering techniques.
  • Experience with AI safety and ethical considerations.

APPLICANTS WITH DISABILITIES

To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo.

WELLS FARGO RECRUITMENT AND HIRING REQUIREMENTS:

a. Third-Party recordings are prohibited unless authorized by Wells Fargo.
b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process

Responsibilities

ABOUT THIS ROLE:

At Wells Fargo, we are looking for talented people who will put our customers at the center of everything we do. Help us build a better Wells Fargo. It all begins with outstanding talent. It all begins with you.
We are seeking a highly motivated and experienced Senior AI Engineer to join our growing team. In this role, you will be responsible for designing, developing, and deploying cutting-edge AI solutions to solve complex business problems. You will work closely with cross-functional teams, including product managers, data scientists, and software engineers, to deliver innovative and impactful AI-powered products and services. You will be a technical leader, mentoring junior engineers and contributing to the overall AI strategy of the company.
Learn more about the career areas and lines of business at wellsfargojobs.com.

IN THIS ROLE, YOU WILL:

  • Lead the development of AI-powered products and services, from concept to deployment.
  • Collaborate with product managers and other stakeholders to define product requirements and translate them into technical specifications.
  • Work with data scientists to identify and acquire relevant data for training machine learning models.
  • Develop and maintain production-ready code and infrastructure for deploying AI models.
  • Mentor junior AI engineers and provide technical guidance.
  • Contribute to the development of the company’s AI strategy and roadmap.
  • Participate in code reviews and contribute to the improvement of our engineering practices.
  • Troubleshoot and resolve issues related to AI models and infrastructure.
  • Document your work and share your knowledge with the team.
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