Lead AI Ops Engineer - Application

USAA•San Antonio, TX

1d•$127,310 - $243,340•Onsite

About The Position

The Lead AI Ops Engineer owns the technical design and architecture for the domain’s most ambiguous or consequential AIOps builds, while continuing to write and ship production code. The role establishes reusable technical standards and patterns for feature engineering, model evaluation, and remediation automation, and helps determine which use cases are ready to advance toward guarded or self-healing automation. The engineer owns the evidence package supporting those decisions and serves as a technical authority for Senior engineers and as a trusted reviewer for the Director on technical bets presented to Risk and Audit. The role is the primary technical escalation point during major incidents, including making real-time decisions about halting automation, and leads postmortems that translate lessons into updated standards. It also mentors Senior engineers and develops future technical leadership. The position is based in San Antonio, Texas, with an onsite requirement of five days per week. Relocation assistance is not available.

Requirements

Bachelor’s degree, or four years of relevant education and/or experience.
Seven or more years of hands-on software or data engineering experience, including sustained ownership of production systems at meaningful scale.
Track record as a team’s de facto technical authority, including leading technical design reviews and setting engineering standards for senior-level engineers.
Deep expertise productionizing ML models for operational use cases using frameworks such as TensorFlow, PyTorch, or scikit-learn, plus advanced fluency with LLM-based techniques and their failure modes, including setting guardrails and evaluation criteria.
Demonstrated experience designing and defending production automation executed against a regulated institution’s production systems, including defensible approval-gate and rollback designs.
Demonstrated judgment under real incident pressure, including experience and credibility to halt automation during an incident.

Nice To Haves

Experience establishing technical standards, architecture patterns, and engineering practices for AIOps solutions adopted across engineering teams.
Experience serving as a senior technical escalation point for production incidents and providing direction and decisions for complex automation and operational AI solutions.
Experience designing and implementing scalable evaluation, safety, and control frameworks for operational AI adopted across multiple teams or functions.
Experience designing or operating highly autonomous or self-healing remediation capabilities, including controls, governance, validation, and evidence needed for production approval.
Experience representing engineering in engagements with Model Risk Management, Internal Audit, or similar governance functions and resolving technical, risk, and control considerations.
US military experience gained through military service or as a military spouse/domestic partner.

Responsibilities

Own technical design and architecture for the domain’s highest-ambiguity or highest-consequence AIOps builds, personally shipping the hardest components.
Set technical standards and reusable patterns for feature engineering, model evaluation, and remediation automation.
Lead the domain’s progression toward higher automation autonomy, deciding with the Director which use cases are ready to advance and owning the supporting evidence package.
Serve as the primary technical escalation point during major incidents, make real-time decisions about the kill switch, and lead postmortems that update standards.
Mentor Senior engineers on technical depth and judgment, develop future technical leadership, and regularly ship production code.