Digital/Technical Product Manager Lead- AI Ops

USAA•San Antonio, TX

2d•Onsite

About The Position

USAA is seeking a Digital/Technical Product Manager Lead to define and drive the product strategy, roadmap, and prioritized use-case backlog for AIOps capabilities across application and infrastructure domains. This individual-contributor role determines what gets built and why, leading use-case prioritization, AIOps platform and build-versus-buy decisions, and the definition of adoption and value metrics. The role applies technical knowledge of LLMs, model risk, AI governance, and autonomous operations to evaluate AI-specific tradeoffs and guide product decisions. Success is measured by a value-driven roadmap and measurement framework that supports engineering execution and demonstrates the business and operational impact of AIOps investments. The position is based in San Antonio, Texas, with a flexible working environment and an on-site requirement of five days per week. Relocation assistance is not available. USAA does not provide visa sponsorship for this role.

Requirements

Bachelor's degree, or four years of relevant education and/or experience.
At least five years of product management experience, including some experience with a technical, data, or AI/ML product.
Demonstrated experience writing and defending a business-value-based prioritized backlog, including discontinuing items that do not deliver.
Working technical fluency in LLMs, ML model lifecycles, and practical limitations sufficient to evaluate engineering claims.
Experience making or materially informing build-versus-buy decisions for a technology capability.
Experience defining and tracking adoption or value metrics for a product or capability.
Comfort working in a regulated environment and sufficient familiarity with model risk or compliance concepts to engage Risk and Audit as a credible partner.
Comfort working without formal authority over the engineers responsible for prioritized work.

Nice To Haves

Experience owning product strategy and lifecycle for AI- or ML-enabled capabilities, from early development through production deployment, adoption, and measurable value realization.
Experience making strategic capability and platform decisions, evaluating build, buy, reuse, and integration options.
Ability to make data-driven prioritization and investment decisions, including recommending discontinuation or deprioritization when value, feasibility, risk, or strategic alignment does not support continued investment.
Experience designing and implementing value-measurement frameworks for emerging technology capabilities, including adoption, operational, and business-outcome metrics.
Experience representing technical products to executive stakeholders and translating complex capabilities and outcomes into business value for funding, investment, and prioritization decisions.

Responsibilities

Own and prioritize the AIOps use-case backlog across application and infrastructure domains, documenting a business-value case for selected items and a reason for items that are not selected.
Prepare value cases for proposed use cases before engineering commits meaningful effort, including adoption and success metrics.
Recommend build-versus-buy approaches and platform selections for AIOps capabilities, including choices of LLM or model families, in partnership with the Platform/MLOps Engineer and both Directors.
Own and revisit decisions about whether specialized platform AI capabilities should reside in an owning platform team or be centralized under AIOps.
Gather and synthesize requirements from AIOps consumers, including Availability, SRE, ServiceNow, and other operations pillars.
Report use-case-level adoption and value data to the AVP.