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USAA

Sells insurance and banking to military families

Lead AI Ops Engineer - Application

Applied Machine LearningUpdated on Nov 5
Full-timeSan Antonio, TX, USA

About the Job

Requirements

  • A bachelor's degree, or four years of relevant education and/or experience.
  • At least seven years of hands-on software or data engineering experience, including sustained ownership of production systems at meaningful scale.
  • A track record of serving as the de facto technical authority on a team, leading technical design reviews, and setting engineering standards for senior-level engineers.
  • Deep expertise productionizing machine-learning models for operational use cases using frameworks such as TensorFlow, PyTorch, or scikit-learn, plus advanced fluency with large-language-model 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 the experience and credibility to decide when to halt an automation mid-incident.

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, including feature-engineering conventions, model-evaluation harnesses, and remediation-automation scaffolding, for Senior and Associate engineers.
  • Lead the domain’s progression toward guarded or self-healing automation with the Director, deciding which use cases are ready and owning the supporting evidence package.
  • Serve as the primary technical escalation point during major incidents, make real-time kill-switch decisions, and lead postmortems that update standards.
  • Mentor Senior engineers on technical depth and judgment, develop future technical leads, and regularly ship production code.
  • Represent engineering in engagements with Model Risk Management, Internal Audit, or similar governance functions, articulating and resolving technical, risk, and control considerations.

Desired Qualifications

  • Establish technical standards, architecture patterns, and engineering practices for AIOps solutions adopted across engineering teams.
  • Serve as a senior technical escalation point for production incidents and provide technical direction and decision-making for complex automation and operational AI solutions.
  • Design and implement scalable evaluation, safety, and control frameworks for operational AI adopted across multiple teams or functions.
  • Design or operate highly autonomous or self-healing remediation capabilities, including the technical controls, governance, validation, and evidence needed for production approval.
  • Have U.S. military experience gained through military service or as a military spouse or domestic partner.

About the Company

USAA

Sells insurance and banking to military families

USAA sells insurance, banking and investment products to U.S. military members, veterans and their families, and membership is limited to that community and eligible relatives. It began when Army officers who struggled to get car coverage agreed to insure each other, and auto and home insurance remain its core business. Members can also open checking and savings accounts, carry credit cards, take out auto loans and mortgages, and buy life insurance, annuities and retirement accounts. The company earns money from insurance premiums, loan interest, card fees and investment management. USAA was founded in 1922 and is based in San Antonio, Texas.

Company size
10,001+
Company stage
Not listed
Total funding
Not listed
Headquarters
San Antonio, TX
Founded
1922

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