below marketmost similar roles pay hereabove market
This role pays less than
90%
of similar roles. Most pay
$128,005–$239,400
— the blue band above.
At the midpoint, this role pays about
$112k
versus about
$184k
for comparable roles.
Based on 240 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
65 open roles
on FindRole.
Listed pay typically runs
$114,080–$218,030
across 42 roles with salary data.
As a Context Engineer, you will join a team focused on the frontier of generative AI, LLMs, and autonomous agents. You will act as an architect of prompts, workflows, and agent behaviors, bridging the gap between human intent and machine execution. Your daily responsibilities include designing and optimizing prompt architectures, context windows, and retrieval-augmented generation pipelines. You will engineer and monitor autonomous AI agents while applying qualitative and quantitative evaluation frameworks to assess model behavior, hallucinations, and latency. You must utilize Python, SQL, and APIs to query data sources while leveraging orchestration frameworks like LangChain, LlamaIndex, or Semantic Kernel. The role requires managing AI risk, ensuring safety, and maintaining compliance with regulatory standards to solve complex business objectives through structured data and logic.
Translate complex business objectives into effective AI and agentic workflows.
Design, test, and optimize prompt architectures, context windows, and RAG pipelines.
Engineer and monitor autonomous or semi-autonomous AI agents for continuous refinement.
Apply qualitative and quantitative evaluation frameworks to assess model behavior and output quality.
Adhere to risk, safety, and agent control design standards for ethical AI deployment.
Document system instructions, prompt templates, agent logic, and testing frameworks.
Identify, measure, and control risks associated with AI operations and data leakage.
What we're looking for
Bachelor's degree in Computer Science, AI, Data Science, Software Engineering, Information Systems, or a related technical/quantitative field.
4 years of relevant education and/or technical experience.
Advanced degree in Computer Science, AI, Data Science, or a related quantitative/technical discipline.
2+ years of hands-on experience with modern AI/ML technologies, data analytics, or software development involving LLM applications, prompt engineering, or workflow automation.
Demonstrated experience with Large Language Models (LLMs), prompt engineering patterns, and major foundation model APIs or open-weights models.
Practical familiarity with AI orchestration frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel) and vector databases.
Proficiency in Python and modern data manipulation tools to query structured/unstructured data sources via SQL or APIs.
Solid understanding of AI risk management, guardrails, security best practices, and agent control design.
Python
R
SQL
NoSQL
Machine Learning
Natural Language Processing
Spark
Kafka
Hadoop
Hive
EMR
MySQL
dbt
Databricks
MapReduce
Gurobi
Data Mining
Data Visualization
Digital Experience Monitoring (DEX)
Telemetry
SQL
Data Analytics
Dashboarding
ITSM Platforms
KPI Development
Root Cause Analysis
Data Integration
Automation
Microsoft 365
AI
Data Solution Architecture
Endpoint Telemetry
Digital Experience Design