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Senior Test Automation AI Engineer (Automation & Operations) - Vice President - Dallas

Dallas, TX, US • Posted 14 hours ago • Updated 1 hour ago

Full Time

On-site

Fitment

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Job Details

Skills

Automated Testing
Quality Assurance
Large Language Models (LLMs)
Apache Velocity
Scripting
UI
API
Workflow
JIRA
Public Relations
Systems Architecture
Test Suites
Machine Learning (ML)
Risk Analysis
Orchestration
Generative Artificial Intelligence (AI)
Privacy
Performance Testing
Evaluation
Continuous Integration
Continuous Delivery
Collaboration
Artificial Intelligence
Microservices

Summary

Job Description

Role Overview:

In the rapid development landscape of 2026, the role of a Senior AI/ML Engineer in test automation is to transform Quality Assurance (QA) from a reactive bottleneck into a proactive, intelligent layer. By leveraging Large Language Models (LLMs) and agentic workflows, you will build a "self-healing" test harness that provides the confidence needed for continuous, high-velocity deployments.

Responsibilities:

Autonomous Test Harness Engineering: Design and maintain "self-healing" test frameworks that use AI to automatically update locators and scripts when UI or API schemas change, reducing maintenance toil by up to 70%.
LLM-Powered Test Generation: Implement agentic workflows (using frameworks like LangGraph or CrewAI) to analyze Jira stories, PR diffs, and system architecture to generate comprehensive test suites, including edge cases and negative scenarios.
Intelligent Observability & Monitoring: Build telemetry pipelines that use ML for anomaly detection and predictive risk analysis, identifying high-risk code areas before they reach production.
Synthetic Data Orchestration: Leverage Generative AI to create high-fidelity, privacy-compliant synthetic datasets for complex integration and performance testing.
"LLM-as-a-Judge" Implementation: Establish automated evaluation frameworks (e.g., Giskard, DeepEval) to measure the accuracy, safety, and hallucination rates of AI-driven features.
CI/CD Integration: Architect intelligent gates within the CI/CD pipeline that use predictive test selection to run only the most relevant tests for a given code change, optimizing execution speed.
Cross-Functional Collaboration: Partner with developers and data scientists to ensure "testability" is built into AI models and microservices from the design phase.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 10121118
Position Id: 9728444cfcf801ff9f5cf1793bab9eb9
Posted 14 hours ago

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