Mistral AISingapore3h ago
Wells FargoPosted 2d ago
Principal AI Engineer at Wells Fargo scores 94 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.
AI in this role
About this role:
Wells Fargo is seeking a Principal AI Engineer to join the CCIBT Gen AI team, which is responsible for building AI frameworks, intelligent agents, and technology platforms that enable and accelerate AI-driven capabilities across CCIBT. As part of the organization's transformation initiatives, you will leverage Generative AI to accelerate software development, enhance engineering productivity, and deliver innovative solutions. In this role, you will design, develop, and deploy cutting-edge artificial intelligence solutions using large language models (LLMs), agentic frameworks, and other emerging technologies. You will be responsible for ensuring that AI solutions are designed and implemented in compliance with Wells Fargo enterprise architecture, security, risk, governance, and responsible AI standards. The ideal candidate will have experience building and operationalizing AI-powered applications, with deep expertise in Agentic AI solutions, Fine Tuning, Retrieval-Augmented Generation (RAG), multi-agent frameworks, scalable AI platform development, and enterprise-grade AI governance and compliance.
In this role, you will:
- Design, develop, and deploy AI applications using LM's, agents, agentic framework, and other related technologies
- Collaborate with enterprise teams to integrate LLM models with the existing CCIBT products and systems
- Lead the design and development of scalable AI applications, ensuring high performance, accuracy, and reliability
- Define benchmarks with metrics to evaluate the performance of agents and agentic frameworks
- Stay up to date with the latest advancements in AI, LLM, agentic frameworks and apply this knowledge to improve existing systems and develop new ones
- 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
- Act as an advisor to leadership to influence AI development strategies, while creating reusable components and tools to enhance efficiency and scalability across CCIBT
Required Qualifications:
- 7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
- 7+ years of experience in software development
- 5+ years of Java, Python, OpenShift containers, and other relevant technologies
- 5+ years of AI and ML concepts, including deep learning, natural language processing and computer vision
Desired Qualifications:
- Bachelor’s or master’s degree in computer science, artificial intelligence or a related field
- Hands-on experience designing and building Generative AI and Agentic AI solutions using Large Language Models (LLMs), multi-agent frameworks, Retrieval-Augmented Generation (RAG), and AI orchestration platforms
- Experience with AI technologies and platforms such as Google Vertex AI, Microsoft 365 Copilot, Copilot Studio, LangChain, Google Agent Development Kit (ADK), AutoGen, Semantic Kernel, or similar frameworks for building enterprise-grade Generative AI and Agentic AI solutions
- Strong proficiency in software engineering using Python, Java or other modern programming languages, with experience building scalable, production-grade applications and APIs
- Experience with cloud-native architectures, microservices, containerization technologies (Docker/Kubernetes), and CI/CD pipelines
- Knowledge of AI evaluation and benchmarking techniques, model performance assessment, and observability frameworks for production AI systems
- Excellent problem-solving and analytical skills with the ability to troubleshoot and resolve complex technical challenges in distributed and AI-driven systems
- Demonstrated ability to independently drive complex initiatives from conception to delivery with minimal guidance, effectively navigating ambiguity, influencing stakeholders, and delivering measurable business outcomes
- Strong collaboration, communication, and stakeholder management skills, with the ability to work effectively across engineering, product, architecture, risk, and business teams
- Demonstrated ability to drive innovation, influence technical direction, and mentor engineers in adopting modern AI and software engineering practices
Job Expectations:
- This position offers a hybrid work schedule
- This position is not eligible for Visa sponsorship
- Relocation assistance is not available for this position
Location:
125 High St. - Boston, Massachusetts 02110
300 S Brevard Street, Charlotte, NC 28202
Pay Range
Reflected is the base pay range offered for this position. Pay may vary depending on factors including but not limited to demonstrated examples of prior performance, skills, experience, or work location. Employees may also be eligible for incentive opportunities.
$191,000.00 - $305,000.00
Benefits
Wells Fargo provides eligible employees with a comprehensive set of benefits, many of which are listed below. Visit Benefits - Wells Fargo Jobs for an overview of the following benefit plans and programs offered to employees.
- Health benefits
- 401(k) Plan
- Paid time off
- Disability benefits
- Life insurance, critical illness insurance, and accident insurance
- Parental leave
- Critical caregiving leave
- Discounts and savings
- Commuter benefits
- Tuition reimbursement
- Scholarships for dependent children
- Adoption reimbursement
Posting End Date:
27 Oct 2026*Job posting may come down early due to volume of applicants.
We Value Equal Opportunity
Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.
Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit’s risk appetite and all risk and compliance program requirements.
Applicants with Disabilities
To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo.
Drug and Alcohol Policy
Wells Fargo maintains a drug free workplace. Please see our Drug and Alcohol Policy to learn more.
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.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- How do you decide that one model's output is better than another's for a given task?
- Walk me through a computer vision problem you solved, from raw data to a deployed model.
- What NLP problem have you worked on, and how did you measure whether it actually worked?
Adapt your resume
- List these exact terms on your resume: Rag, Fine Tuning, AI Evaluation, Computer Vision, and Nlp. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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