Senior Artificial Intelligence Solutions Consultant

About this role:

Wells Fargo is seeking a Senior Artificial Intelligence Solutions Consultant to support the implementation of generative AI capabilities for data, analytics, and decision sciences. This role combines hands-on technical skills with project-level consulting to help decision science teams refine use cases, develop and test prototypes, and responsibly use approved Gen AI tools and automation. The consultant will work within defined objectives, collaborate with immediate team members and business partners, and contribute reusable components and documentation that improve analytics and modeling workflows while following applicable quality, risk, and governance requirements.

In this role, you will:

Contribute as an individual consultant to moderately complex Gen AI initiatives for data, analytics, modeling, and decision science teams

Collaborate with decision science practitioners and business partners to refine Gen AI and automation use cases based on defined business needs, technical feasibility, data readiness, risk, and adoption considerations

Develop and test Gen AI prototypes that improve analytical workflows, including data discovery and preparation, code generation and review, exploratory analysis, model development support, documentation, monitoring, knowledge retrieval, and repeatable reporting

Apply prompt engineering, retrieval-augmented generation, agentic workflow, semantic retrieval, evaluation, and human-in-the-loop techniques using approved tools and established patterns

Translate defined business and analytical requirements into technical tasks, prototype approaches, test plans, success measures, and implementation activities with guidance from more experienced team members

Build and maintain reusable prompts, evaluation scripts, automation components, and technical documentation for use within assigned projects or workstreams

Participate in technical working sessions, demonstrations, peer reviews, and knowledge-sharing activities with data scientists, analysts, model developers, product partners, and control partners

Perform structured testing and evaluation of solution outputs for accuracy, relevance, robustness, traceability, security, responsible AI considerations, and readiness for the intended use

Work with immediate business, data, technology, model risk, compliance, and control partners to apply established standards and complete required review and governance activities

Analyze technical issues, document options and tradeoffs, escalate decisions outside assigned authority, and communicate progress and recommendations clearly to project leads and business partners

Required Qualifications:

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

Desired Qualifications:

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:

8 Nov 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 com