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Senior Artificial Intelligence Solutions Consultant

ExperiencedNo visa sponsorship

Posted 9 days ago

No clicks

**Senior AI Solutions Consultant at Wells Fargo:** Drive generative AI integration in data, analytics, and decision science teams. Key responsibilities include consultant-driven Gen AI projects, use case refinement with stakeholders, testing AI prototypes, applying AI techniques like prompt engineering and semantic retrieval, and collaborating on reusable components and documentation. Must-have skills: 3+ years in AI, Python, SQL, Gen AI implementation, and strong communication.

Compensation
Not specified

Currency: Not specified

City
Not specified
Country
Not specified

Full Job Description

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 commensurate with the business units 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.

c. Please be prepared to provide accurate information and supporting documentation in connection with any lawful employment and education verification conducted by Wells Fargo.


Senior Artificial Intelligence Solutions Consultant

Compensation

Not specified

City: Not specified

Country: Not specified

Wells Fargo Corporate & Investment Banking  logo
Investment Banking

9 days ago

No clicks

at Wells Fargo Corporate & Investment Banking

ExperiencedNo visa sponsorship

**Senior AI Solutions Consultant at Wells Fargo:** Drive generative AI integration in data, analytics, and decision science teams. Key responsibilities include consultant-driven Gen AI projects, use case refinement with stakeholders, testing AI prototypes, applying AI techniques like prompt engineering and semantic retrieval, and collaborating on reusable components and documentation. Must-have skills: 3+ years in AI, Python, SQL, Gen AI implementation, and strong communication.

Full Job Description

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 commensurate with the business units 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.

c. Please be prepared to provide accurate information and supporting documentation in connection with any lawful employment and education verification conducted by Wells Fargo.