Senior Artificial Intelligence Solutions Consultant
Wells Fargo
- Location
- Bengaluru, India
- Work model
- On-Site
- Level
- Senior
- Posted
- Aug 12, 2026
Skills
About this role
About this role: Wells Fargo is seeking a Senior Artificial Intelligence Solutions Consultant who provides flexible/elastic offshore prompt-engineering capacity supporting the applied-AI team. Builds and iterates prompts for point solutions within horizontal toolsets (i.e. copilot, Copilot Studio) and within low code/no code tools i.e. Tachyon AI Studio (claude code/devin if available). Runs rapid experiments and prototype iterations under the direction of the Lead Applied AI Business Architect; and supports evaluation and quality checks. 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 4+ years of software engineering experience, with strong expertise in designing and delivering enterprise-scale applications and platforms. Expert-level Python programming skills, including: Object-Oriented Programming (OOP), Design Patterns, Multithreading and Asynchronous Programming, API Development (FastAPI, Flask), Scripting and Automation, Performance Optimization and Debugging, Strong experience in Data Engineering and Data Processing, Experience with Spark, Pandas, and distributed data processing frameworks, CI-CD deployments, Agile principles 2+ years of hands-on experience building production-ready Generative AI and LLM-based solutions expertise in: GPT Models and Enterprise LLMs, LangChain, LangGraph, Retrieval-Augmented Generation (RAG), Agentic AI and Multi-Agent Systems, Prompt Engineering, Embedding Models, Vector Search and Semantic Retrieval Experience building enterprise AI applications such as: AI Assistants and Copilots, Intelligent Chatbots, Knowledge Retrieval Platforms, AI-Powered Automation Solutions, Document Intelligence Systems Hands-on experience with vector databases and search technologies such as Pinecone, OpenSearch, FAISS, ChromaDB, or equivalent platforms. Strong understanding of NLP, information retrieval, semantic search, and knowledge management systems. Experience designing and implementing REST APIs, microservices, and cloud-native applications. Strong experience with cloud platforms such as GCP, including AI/ML services and scalable deployment architectures. Experience with database technologies including SQL, NoSQL, Graph Databases (Neo4j), and data modelling. Strong understanding of software engineering best practices, including CI/CD, testing, code reviews, security, observability, and DevOps practices.
Desired Qualifications
Critical Must-Have Skills Python Development & Scripting Data Engineering & ETL Pipelines Solution Design API Development & Microservices Posting End Date: 19 Aug 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