AI Quality Engineer
Listed on 2026-02-10
-
IT/Tech
AI Engineer, Data Analyst
Overview
For more details, please connect with Ibad Ullah Khan at or email at .
End Client:
New York City Department of Social Services
Job Title: AI Quality Engineer
Duration: 36 - 60 Months
Start Date: ASAP
Location:
Brooklyn, NY 11238 (Onsite)
Position Type:
Contract
Interview Type:
Webcam
Requirement # DSS-ITS-C--1
Ceipal
Description: The SNAP Payment Error Rate (CAP) Reduction project for NYC DSS focuses on improving the accuracy, compliance, and efficiency of SNAP benefit processing. The initiative leverages AI-driven solutions, system integrations, and advanced automation to reduce payment errors, enhance program integrity, and ensure adherence to federal and state regulations while improving service delivery for beneficiaries. As an AI Quality Engineer, you are responsible for validating AI-powered systems supporting SNAP processing by designing intelligent test scenarios, analyzing PRDs, and ensuring end-to-end quality across applications.
The role includes AI-driven automation, API testing, performance validation, workflow analysis, and identifying automation opportunities to improve system reliability, scalability, and compliance.
Tasks & Duties:
- AI Agent Test Scenario Creation: Designing robust and relevant test scenarios to validate AI agent behavior and performance.
- PRD Analysis: Analyzing Product Requirement Documents (PRDs) to extract testing requirements and ensure comprehensive test coverage.
- Performance Testing: Conducting thorough performance testing of AI systems to identify bottlenecks and ensure scalability.
- Agentic Tool: Utilizing agentic tools such as Windsurf, Claude Code, and Cursor for advanced automation tasks.
- Selenium AI Plugins: Implementing and leveraging AI-powered Selenium plugins, including Healenium and Applitools Eyes, for intelligent visual and functional testing.
- QA Automation with MCP Integration: Integrating QA automation processes with our Master Control Program (MCP) for centralized management and execution.
- APIs & Integrations: Testing and integrating with REST and SOAP APIs to ensure seamless connectivity between systems.
- Process Analysis & Workflow Analysis: Analyzing complex business workflows to understand processes and identify pain points.
- Identifying Automation Opportunities: Proactively identifying areas within the QA lifecycle and business processes that can be optimized through AI automation.
- Excel Automation: Automating data-intensive tasks using Excel automation techniques
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