Senior Artificial Intelligence Solutions Consultant
Wells Fargo is hiring a Senior Artificial Intelligence Solutions Consultant in Hyderabad, India. Level rates it ; you can apply on Wells Fargo.
Level's read on this job
- Works on AI ●●●○ is how Level rates this AI consultant role: the daily work is on AI products, without building the model.
- Tools and skills the posting cites include Copilot, LangChain and LangGraph.
- Level classifies it as a senior role.
- Level lists 1,500+ other open roles at Wells Fargo.
- The role was posted in the last few days.
AI in this role
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 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.
c. Please be prepared to provide accurate information and supporting documentation in connection with any lawful employment and education verification conducted by Wells Fargo.
How we rate this
Senior Artificial Intelligence Solutions Consultant at Wells Fargo rates 64 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in AI consultant jobs at this level
Pay
- Typical AI consultant job
- $152k
This posting doesn't list pay. Use the typical AI consultant figure when pay comes up. See AI consultant jobs
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How do you decide that one model's output is better than another's for a given task?
- How do you think about the risk of an AI system in this kind of role failing silently?
Adapt your resume
- List these exact terms on your resume: Prompt engineering, RAG, AI agents, AI Evaluation, and AI Safety. 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.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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