AI Platform Architect, Principal

USAA

Confirmed live 2 days ago High trust
Closes in 3 days Hybrid

Quick summary

Work type
Hybrid
Location
San Antonio, TXPlano, TXPhoenix, AZ
Salary
$164,780–$305,780 / yr
Posted
7 days ago
Freshness
Confirmed live 2 days ago
Closes
Sep 14, 2026 (soon)

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $208k
This role $235k
$123k most similar roles pay here $325k

This role pays more than 69% of similar roles. Most pay $169,550–$245,800 — the shaded band above. At the midpoint, this role pays about $235k versus about $208k for comparable roles.

Based on 239 similar postings.

Employer

About USAA

USAA (United Services Automobile Association) is a San Antonio-based Fortune 500 financial services company founded in 1922, dedicated to providing insurance, banking, and investment solutions exclusively to U.S. military members, veterans, and their families.

USAA currently has 14 open roles on FindRole.

Listed pay typically runs $143,320–$273,930 across 14 roles with salary data.

Most-posted roles

View all roles at USAA

At a glance

TL;DR · AI Platform Architect, Principal

As a Principal AI Platform Architect, you will lead the strategy, architecture, and evolution of the enterprise AI platform to enable generative AI, agentic AI, machine learning, and advanced analytics across the organization. You will collaborate with business and technology leaders to define scalable, secure, and compliant capabilities while establishing governance frameworks, architecture standards, and multi-year roadmaps. Your daily work involves designing systems, services, and dataflows, performing risk assessments, and providing technical mentorship to engineers. The role requires expertise in platform engineering, data architecture, and software engineering within highly regulated environments. You will utilize technologies such as AWS Bedrock, OpenAI, Anthropic, and foundation model ecosystems to build agent architectures, orchestration frameworks, and knowledge management systems including vector search and knowledge graphs. This position solves the challenge of delivering responsible AI at scale while ensuring robust security and operational excellence.

What you'll do

  • Lead the strategy, architecture, and evolution of the enterprise AI platform to support generative AI and machine learning.
  • Define scalable, secure, and compliant architecture standards for AI capabilities across multiple business functions.
  • Establish governance frameworks and multi-year roadmaps to accelerate innovation and drive adoption of emerging technologies.
  • Partner with executive leadership to influence the funding, priority, and execution of architectural solutions.
  • Conduct formal assessments of domain applications to identify risks, strengths, and opportunities for improvement.
  • Provide technical mentorship and guidance to architects and engineers to ensure team redundancy and growth.
  • Manage risk assessment methodologies to evaluate and approve architecture standards in a highly regulated environment.
  • Maintain external relationships with industry organizations, vendors, and government boards to stay current on technology trends.

What we're looking for

  • 10+ years of experience in technology architecture, platform engineering, software engineering, data architecture, or related disciplines.
  • Experience leading enterprise-scale technology transformation initiatives and defining multi-year roadmaps for emerging technologies.
  • Expertise in architecting AI, machine learning, generative AI, and advanced analytics platforms with a focus on governance and security.
  • Proven ability to partner across cross-functional teams including risk, security, legal, and business units to establish operating models.
  • Deep understanding of technology governance, architecture principles, and risk management within highly regulated industries.
  • Experience designing agent architectures, orchestration frameworks, and knowledge architectures like vector search or knowledge graphs.
  • Ability to communicate complex technical strategies and risks to both technical teams and executive leadership.
  • Demonstrated ability to mentor engineers and provide thought leadership in the AI space.

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