Lead AI Ops Architect for Infrastructure & Autonomy

USAA Life Insurance Company

San Antonio (TX)

Hybrid

USD 170,000 - 250,000

Full time

4 days ago
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Job summary

USAA Life Insurance Company is seeking a Lead AI Ops Engineer - Infrastructure in San Antonio, TX. The role focuses on owning the toughest design decisions, defining standards for telemetry pipelines and IaC scaffolding, and advancing infrastructure use cases toward autonomy.

You will mentor engineers and stay hands-on with production code and automation. The position demands 7+ years in infrastructure or site reliability engineering, experience with ML-enabled production systems, and strong

Qualifications

  • Bachelor's degree or equivalent in a relevant field or equivalent work experience.
  • Proven track record as a technical authority and leader in design reviews.
  • Hands-on experience with scalable production systems and infra automation.

Responsibilities

  • Own the technical design and architecture for high-ambiguity AIOps workloads.
  • Set standards and reusable patterns for telemetry pipelines and infra-as-code patterns.
  • Lead advancement of infrastructure use cases toward higher autonomy with evidential justification.
  • Act as primary escalation point during major incidents and drive postmortems.
  • Mentor senior engineers while continuing to ship production code and IaC.

Skills

Senior technical authority
Productionizing ML models
Incident response judgment
Leadership in design reviews
Hands-on infrastructure

Education

Bachelor's degree or equivalent
4 years relevant education/experience

Tools

Terraform
Ansible
Kubernetes operators

Job description

USAA Life Insurance Company is seeking a Lead AI Ops Engineer - Infrastructure in San Antonio, TX. The role focuses on owning the toughest design decisions, defining standards for telemetry pipelines and IaC scaffolding, and advancing infrastructure use cases toward autonomy.

You will mentor engineers and stay hands-on with production code and automation. The position demands 7+ years in infrastructure or site reliability engineering, experience with ML-enabled production systems, and strong

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