AVP, AI Operations

USAA•San Antonio, TX

1d•$195,230 - $351,410•Hybrid

About The Position

The AVP, AI Operations is responsible for defining and executing the association strategy for Artificial Intelligence for IT Operations (AIOps), intelligent automation, operational analytics, and autonomous operations capabilities across the association. This leader serves as the strategic owner of future-state operational transformation, driving the evolution of technology operations from reactive and manual processes toward predictive, data-driven, and increasingly autonomous service management practices. The AVP partners closely with Availability Management, Site Reliability Engineering (SRE), Infrastructure, Engineering, Architecture, Data & Analytics, Information Security, and Association Technology leaders to design and implement next-generation operational capabilities that improve service reliability, accelerate issue resolution, reduce operational risk, and enhance organizational efficiency. The role is accountable for developing the frameworks, platforms, automation capabilities, and operating models that enable intelligent operations at scale while ensuring alignment with association AI policies, risk management, and technology strategy.

Requirements

Bachelor's degree; OR 4 years of relevant education and/or experience.
10 years of progressive experience in technology operations, automation, engineering, platform operations, analytics, AIOps, or related disciplines.
6 years of people leadership experience in building, managing and/or developing high performing teams required.
Demonstrated success implementing association-scale automation and operational intelligence solutions.
Advanced experience leading large-scale technology transformation and modernization initiatives.
Experience designing and implementing observability, analytics, and AIOps platforms.
Experience leveraging machine learning, predictive analytics, and automation to improve operational performance.
Strong understanding of cloud operations, distributed systems, SRE principles, and service management frameworks.
Experience influencing executive stakeholders and driving association-wide change initiatives.
Knowledge of AI governance, risk management, and responsible AI practices.
Exceptional strategic thinking, innovation, communication, and organizational leadership skills.

Nice To Haves

Association AIOps & Automation Transformation Leadership
Observability, SRE, Cloud & Modern Operations Expertise
Executive-Level Strategy & AI Governance

Responsibilities

Define and execute association AIOps strategy, roadmap, and target operating model.
Lead the transformation from traditional operations to predictive, intelligent, and autonomous operational capabilities.
Establish long-term strategic priorities for automation, operational intelligence, observability, and AI-enabled service operations.
Identify emerging technologies and industry best practices that can improve operational effectiveness and service reliability.
Influence investment decisions related to AIOps platforms, observability solutions, automation technologies, and AI capabilities. Advise executive leadership on operational innovation opportunities and technology transformation strategies.
Develop association standards, operating policies and principles for AIOps.
Establish association capabilities for operational intelligence, event analytics, and data-driven decision making.
Lead efforts to improve event correlation, anomaly detection, alert prioritization, and root-cause identification.
Develop predictive analytics capabilities that identify operational risks before service disruptions occur.
Advance real-time visibility into service health, platform performance, and operational risk exposure.
Develop and execute a comprehensive automation strategy focused on reducing manual intervention and operational toil.
Drive automation adoption across incident, problem, change, and service management processes.
Identify opportunities to eliminate repetitive tasks and optimize operational workflows.
Measure automation effectiveness through productivity, reliability, and risk reduction outcomes.
Leverage machine learning and advanced analytics to improve operational effectiveness and stability. Establish the strategy for association observability capabilities supporting proactive service management.
Partner with SRE, platform engineering, infrastructure teams, and operations teams to implement automated remediation and autonomous recovery capabilities, improve telemetry, monitoring, tracing, and operational visibility.
Drive the integration of operational data across applications, infrastructure, cloud platforms, and business services.
Ensure operational data quality, accessibility, and risk management support AI-driven decision making.
Lead the development of integrated operational platforms that enable predictive and autonomous capabilities. Drive capabilities that anticipate incidents before they impact customers, employees, or business operations.
Improve capacity management, performance optimization, and resiliency planning through predictive intelligence.
Establish controls and oversight mechanisms for operational AI implementation.
Establish KPIs and value realization metrics for automation, operational efficiency, service reliability, and AI adoption.
Build and lead high-performing teams focused on AIOps, automation engineering, operational analytics, and transformation.
Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures.