Lead Applied AI Engineer

Wells Fargo & Company•Iselin, NJ

1d•$159,000 - $305,000

About The Position

The Cognitive AI Solutions team is building the next generation of agentic AI and process intelligence capabilities for the firm. As our platform matures, partner organizations across the bank are engaging with us to bring advanced AI directly to their highest-impact business problems. We are seeking a Lead Applied AI Engineer to partner with a business organization (such as banking operations, complaints, or wholesale operations) to design, build, and ship AI capabilities for one of the bank's most important production domains. This is a hands-on engineering role with significant scope. You will work at the intersection of two organizations: partnering closely with the business domain team, while remaining part of the Cognitive AI Solutions engineering bench. You will be the technical engine that brings our platform capabilities and state-of-the-art models into a high-impact business domain, driving measurable outcomes.

Requirements

5+ years of Specialty Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
5+ years of software engineering experience, with at least 3 years applying machine learning or AI to production systems.

Nice To Haves

Hands-on experience building and deploying machine learning models, including transformer-based architectures or foundation models, in a production environment.
Strong full-stack software engineering skills—comfortable across data, models, services, and integration; able to ship end-to-end.
Solid understanding of modern AI evaluation, observability, and guardrails for production deployment.
Excellent collaboration, technical communication, and problem-solving skills, with a track record of shipping software that touches real users in real production environments.
Prior experience in financial services applications (e.g., banking operations, complaints, wholesale operations) or comparable regulated enterprise domains.
Experience working under Model Risk Management or compliance governance for production AI deployment.
Experience working with large-scale transactional or sequential data.
Experience working in a partner-facing engineering engagement model with business organizations.

Responsibilities

Partner with the business organization to understand their workflows, data, and operational touchpoints, and identify where advanced AI can deliver measurable improvements.
Design and build AI capabilities for the partner domain, applying state-of-the-art techniques, including transformer-based models and foundation models for sequential and transactional data.
Ship and own models in production, integrating platform components into the partner domain, contributing improvements back to the platform team, and ensuring deployed systems meet the bank's reliability, security, and compliance standards.
Build evaluation, observability, and guardrail systems—production AI requires rigorous testing, monitoring, and behavioral controls. You will own these for the systems you ship.
Collaborate across the data and modeling application boundary—deploying models within the modeling environment while consuming data and context from the regulated data platform.
Translate technical progress into presentable outcomes—supporting partner stakeholder reviews and Cognitive AI Solutions executive demos as needed.