Lead AI Ops Engineer - Infrastructure

USAA Life Insurance Company; San Antonio (TX); Hybrid; USD 170,000 - 250,000; Full time

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

Why USAA?

At USAA, our mission is to empower our members to achieve financial security through highly competitive products, exceptional service and trusted advice. We seek to be the #1 choice for the military community and their families.

Embrace a fulfilling career at USAA, where our core values - honesty, integrity, loyalty and service - define how we treat each other and our members. Be part of what truly makes us special and impactful.

We are proud to support active-duty military spouses. USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with applicable policy and business needs.

The Opportunity

The Infrastructure AI Ops team's Senior engineers build and operate the data-to-automation pipeline for individual capacity, anomaly, and remediation use cases.

As the Lead AI Ops Engineer - Infrastructure , you own what's harder than any single use case: the technical judgment calls that don't have an obvious owner - which anomaly-detection or capacity-modeling approach should become the pattern every new infrastructure use case reuses, whether a topology-reconciliation design scales past the next order of magnitude of the estate, what a remediation needs before it's trusted to run at autonomy level 4 against production compute or storage. You'll still write code and ship - this is not a step off the keyboard - but you will also be the person seniors come to when a design doesn't have a textbook answer, and the person the Director turns to when a technical bet needs a second, harder look before it's defended to Risk and Audit.

This position offers a flexible work environment with an onsite requirement of 5 days per week. This position is based in San Antonio, TX. Relocation assistance is not available for this position.

What you'll do:

• Own the technical design and architecture for the domain's highest-ambiguity or highest-consequence AIOps builds, personally shipping the hardest components yourself rather than delegating them away.
• Set the technical standards and reusable patterns - telemetry-consuming feature pipelines, topology-graph design, infrastructure-as-code remediation scaffolding - that the domain's Senior and Associate engineers build against.
• Lead the domain's progression up the autonomy ladder - decide, with the Director, which infrastructure use cases are ready to advance toward guard railed or self-healing automation, and own the evidence package that justifies it.
• Serve as the primary technical escalation point during major incidents - including the real-time call on the kill switch - and lead postmortems that turn the lesson into an updated standard.
• Mentor the domain's Senior engineers on technical depth and judgment, growing the next Lead, and stay hands-on shipping production code and infrastructure-as-code on a regular cadence.

What you have:

• Bachelor's degree; OR 4 years of relevant education and/or experience.
• 7+ years of hands-on infrastructure, platform, or site-reliability engineering experience, including sustained ownership of production systems at meaningful scale.
• A track record of being the de facto technical authority on a team - the engineer others' designs get checked against - including leading technical design reviews and setting engineering standards for senior-level engineers.
• Deep expertise productionizing ML models for infrastructure operational data using frameworks such as TensorFlow, PyTorch, or scikit-learn, plus advanced, hands-on expertise with infrastructure-as-code and orchestration tooling - Terraform, Ansible, Kubernetes operators - including setting team conventions.
• Demonstrated experience designing and defending production automation that has executed against a regulated institution's production infrastructure, including the approval-gate and rollback design that made it defensible.
• Demonstrated judgment under real incident pressure, including the experience and credibility to make the call to halt an automation mid-incident.

What sets you apart:

• Demonstrated experience establishing technical standards, architecture patterns, and engineering practices for Infrastructure AI Ops solutions that are adopted across engineering teams.
• Proven experience serving as a senior technical escalation point during critical production incidents, providing technical leadership and decision-making for complex infrastructure automation solutions.
• Experience designing and implementing operational AI evaluation, safety, and control frameworks that are scalable and adopted across multiple teams or functions.
• Experience designing or operating highly autonomous, self-healing infrastructure capabilities, including automated production remediation and the technical controls, validation, governance, and evidence required to support implementation.
• Demonstrated experience representing engineering in engagements with Model Risk Management, Internal Audit, or similar governance functions, effectively communicating and resolving complex t