About this role:
Wells Fargo is seeking a Principal AI Engineer.
In this role, you will:
- Act as an advisor to leadership to develop or influence applications, network, information security, database, operating systems, or web technologies for highly complex business and technical needs across multiple groups
- Lead the strategy and resolution of highly complex and unique challenges requiring in-depth evaluation across multiple areas or the enterprise, delivering solutions that are long-term, large-scale and require vision, creativity, innovation, advanced analytical and inductive thinking
- Translate advanced technology experience, an in-depth knowledge of the organizations tactical and strategic business objectives, the enterprise technological environment, the organization structure, and strategic technological opportunities and requirements into technical engineering solutions
- Provide vision, direction and expertise to leadership on implementing innovative and significant business solutions
- Maintain knowledge of industry best practices and new technologies and recommends innovations that enhance operations or provide a competitive advantage to the organization
- Strategically engage with all levels of professionals and managers across the enterprise and serve as an expert advisor to leadership
Required Qualifications:
- 7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
Desired Qualifications:
- This is an individual contributor role (Principal AI Engineer) which is at the level of Executive Director
- Own the end-to-end AI/ML lifecycledesign, build, deploy, and maintain scalable agent solutions for Technology Analytics.
- Embed Generative AI and Agentic AI into day-to-day business processes to lift efficiency and employee productivity.
- Execute and refine the AI roadmap, keeping every project tightly aligned with enterprise strategy and measurable KPIs.
- Design autonomous AI agents capable of real-time decision-making and action with minimal human oversight.
- Enforce best-in-class practices for model scalability, reliability, security, and ongoing maintenance.
- Lead R&D on emerging AI tech, scouting fresh use cases to keep Wells Fargo at the innovation forefront.
- Drive cross-division rollout of AI solutions, track impact, and deliver tangible cost- and time-savings.
- Serve as an AI thought leadermentor teams, champion best practices, and translate complex concepts for senior stakeholders.
- 7 years of Analytics, AI or Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education.
- 3+ years of experience in Generative AI tech like Retrieval-Augmented Generation (RAG) design end-to-end pipelines (Vector DBs, chunking, embedding, retrieval, context injection) to ground LLM responses on enterprise knowledge.
- Strong software development skills, particularly in Python, with experience working with AI frameworks (any one of Langchain, Langgraph, CrewAI, Autogen, Google ADK) and tools in cloud environments; Knowledge of ML, NLP, Information Retrieval, Recommender Systems and LLMs. Must havedeployed role-based agent (Multi Agent Orchestration) teams with one of the listed frameworks
- Experience with container & orchestration technologies (Docker, Kubernetes etc) and cloud platforms (AWS, GCP or Azure); Experience with training, fine-tuning, and applying large language models (LLMs) for agentic AI application
- Deployment & MLOps -containerize inference endpoints with Docker/K8s, scale on AWS/GCP GPU instances, and automate CI/CD, canary releases, and rollback strategies.
- 5+ years of experience with NLP Tech/ NLP pipelines (NLTK, spaCy, Hugging Face, BERT/GPT)
- 5+ years of hands-on experience with Microsoft Power Platform (Power Apps, Power Automate, Power BI, Dataverse), including solution architecture, governance, and deployment.
- Working knowledge of enterprise tools like MS Copilot Studio and AgentSpace for Agentic AI, with a strong understanding of prompt engineering, grounding, and extensibility.
- Familiarity with Data Connectors and API gateways that support seamless communication between systems.
- General Analytics Data Visualization using Tableau, PowerBI. Strong knowledge of SQL (Structured Databases)
- Deep subject matter expertise in AI technologies, including but not limited to Copilot Studio, Azure AI Foundry, Google Agent Space, Google Gemini, Microsoft 365, and M365 Copilot.
- Traditional Data Science - classical ML and statistical modelinglinear/logistic regression, time-series ARIMA/Prophet, decision trees, random forests, gradient-boosting (XGBoost/LightGBM), SVMs, k-means and hierarchical clustering, association-rule mining (Apriori), and A/B testing with hypothesis-testing frameworks
- Ability to orchestrate processes across integrated systems to enable robust workflows and seamless operations.
- Ability to collaborate with cross-functional teams to align technical solutions with business goals and end-user needs.
- A strong focus on cybersecurity and risk management throughout the software development lifecycle.
- Passion for designing solutions that prioritize end-user experience and usability.
- Strong problem-solving skills and attention to detail in complex system design.
- Proficiency in designing and developing multi-agent systems where multiple AI agents collaborate to achieve complex tasks
7 Aug 2025
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