Senior Artificial Intelligence Consultant- AI

About this role: Wells Fargo is seeking a Senior Artificial Intelligence Consultant In this role, you will: • Lead cross functional teams to identify, strategize, and execute Artificial Intelligence initiatives within a line of business • Understand the strategy to recommend solutions on solving business challenges • Analyze and review cases obtaining the required resources to ensure the solution delivers the intended benefits • Leverage knowledge to evaluate technological readiness, data availability, and resources to execute the proposed solutions • Influence without authority to drive the implementation of Artificial Intelligence initiatives and programs while serving multiple stakeholders • Decision key issues which may arise during development or implementation • Collaborate and consult with peers, colleagues and managers to resolve and achieve goals Required Qualifications: • 4+ years of Artificial Intelligence experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Desired Qualification • 3+ years of Artificial Intelligence Solutions, data science, advanced analytics, or related consulting experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education •   Experience delivering assigned components of moderately complex projects, working within defined objectives, and coordinating effectively with cross-functional team members •   Hands-on experience applying Generative AI or large language models to data, analytics, modeling, or decision science workflows •   Proficiency in Python and SQL, including data processing, API integration, testing, debugging, and workflow automation •   Experience with at least one of the following: prompt engineering, retrieval-augmented generation, agentic workflows, semantic retrieval, structured outputs, or LLM evaluation methods •   Experience working with analytical data platforms and frameworks such as Pandas, Spark, Databricks, cloud-based AI/ML services, or equivalent technologies •   Experience translating defined business and analytical problems into technical requirements, prototypes, test results, and implementation recommendations •   Strong communication and collaboration skills, including requirements clarification, technical documentation, working-session participation, and the ability to explain technical concepts to immediate team members and business partners •   Foundational understanding of responsible AI, model and data governance, information security, privacy, quality, testing, and human oversight considerations relevant to enterprise AI solutions • Candidates are not expected to have experience in every technology listed below. Strong candidates will typically bring hands-on experience in several of these areas, along with the ability to learn and apply additional tools and patterns on the job. •   Experience supporting data science, quantitative analytics, model development, marketing analytics, or decision intelligence teams •   Experience automating components of analytics or model-lifecycle activities such as data preparation, code migration, model documentation, validation support, monitoring, forecasting, campaign analytics, or insight generation •   Hands-on experience with enterprise AI assistants and development environments such as Microsoft 365 Copilot, Copilot Studio, GitHub Copilot, approved low-code/no-code AI platforms, or comparable tools •   Familiarity with orchestration frameworks such as LangChain or LangGraph and with enterprise LLM, RAG, or agentic solution patterns •   Familiarity with vector databases, semantic retrieval, metadata management, knowledge graphs, or semantic layers that improve LLM grounding in enterprise data and analytical context •   Experience using or supporting REST APIs, lightweight services, reusable Python modules, and cloud-native components for analytics automation •   Familiarity with AI/LLM Ops practices, including versioning, evaluation, observability, testing, deployment controls, and performance monitoring •   Experience with one or more additional capabilities such as knowledge graphs, semantic or metadata layers, advanced RAG or agentic implementation, cloud AI/ML integration, or production deployment practices •   Ability to contribute to reusable standards, playbooks, technical documentation, training materials, and team knowledge-sharing activities Critical Must-have skills: •   Generative AI implementation for data, analytics, and decision science use cases •   Python, SQL, data processing, testing, and analytics workflow automation •   Hands-on experience in one or more of the following: prompt engineering, RAG, agentic workflows, semantic retrieval, structured outputs, or LLM evaluation •   Technical collaboration, requirements clarification, and clear communication with project teams and business partners •   Prototyping, component-level solution design, and use of established implementation patterns •   Foundational awareness of responsible AI, data governance, quality assurance, security, and risk-aware execution Posting End Date: 7 Sep 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. Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates, including women, persons with disabilities, aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process. 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.