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Job Title : Lead AI QA Automation Engineer
Location : Charlotte, NC 28202 (Onsite)
Duration : 12 Months
Job Details:
Job Summary
We are seeking a Senior / Lead AI QA Automation Engineer to drive the next generation of AI-powered test automation using Generative AI and Model Context Protocol (MCP) based solutions. This role will focus on building intelligent systems that ingest user stories, acceptance criteria, and test context from tools such as JIRA, Confluence, APIs, and code repositories, and automatically generate, execute, and maintain UI and API automation.
The ideal candidate will design context-aware, self-healing automation ecosystems using LLMs and MCP to reduce manual effort, improve reliability, and enable true shift-left quality engineering across agile teams.
Key Responsibilities
AI & MCP-Based Test Generation
Design and implement MCP-based AI solutions that provide LLMs structured access to:
User stories and acceptance criteria (JIRA/Confluence) Existing test assets and automation frameworks Application metadata, APIs, and UI locators Use LLMs (e.g., GPT-4, Claude) with MCP to automatically generate:
BDD test scenarios (Gherkin)
Executable UI and API automation scripts Test data and edge-case coverage Ensure generated tests remain context-aware, explainable, and traceable to requirements.
Intelligent Automation Framework Development
Build and enhance AI-driven automation frameworks incorporating:
MCP-based context retrieval for dynamic test generation Self-healing locators and adaptive test flows Automatic test refactoring when application or requirements change Establish standards for scalable, reusable, and maintainable automation.
Shift-Left & Agile Quality Enablement
Enable test creation during story grooming and development sprints using AI-assisted workflows.
Provide immediate feedback to developers via MCP-powered test execution and analysis.
Collaborate closely with product owners, developers, and platform teams.
AI Application & Model Validation
Validate AI-enabled features and systems, including:
Prompt behavior and response quality
MCP context accuracy and relevance
RAG pipelines and tool-based grounding
Non-deterministic outputs and hallucination risks Define validation strategies, scoring thresholds, and acceptance criteria for AI-driven functionality.
UI & API Automation
Develop robust UI automation using Playwright (preferred), Selenium, or Cypress.
Create comprehensive API automation for RESTful services and backend integrations.
Ensure consistency between AI-generated tests and hand-crafted regression suites.
Flaky Test Detection & Optimization
Leverage AI and MCP context to:
Identify flaky tests and root causes
Correlate failures with application, environment, or data changes Automatically recommend or implement fixes Improve overall test suite stability and reliability.
Required Skills & Qualifications:
AI, MCP & Generative Automation
1 years of experience building AI-driven test automation solutions.
Hands-on experience using LLMs with structured context, including:
Model Context Protocol (MCP) or equivalent tool-based/contextual grounding approaches OpenAI APIs, Claude, LangChain, or similar orchestration frameworks MCP Architecture & Tooling:
Experience defining MCP servers, tools, and context sources to safely expose enterprise data to LLMs for test automation use cases.
Prompt Engineering & Context Design:
Ability to design prompts and MCP context boundaries that produce high-quality, deterministic, and auditable test outputs.
AI Output Analysis:
Experience analyzing non-deterministic AI outputs and defining scoring, confidence thresholds, and validation rules.
Desired Skills & Experience:
Automation & Programming
Strong expertise in Playwright (preferred), Selenium, or Cypress.
Proficiency in Python or TypeScript/JavaScript.
Solid knowledge of automation design patterns and test architecture.
BDD & Test Engineering
Extensive experience with BDD frameworks (Cucumber/Gherkin).
Strong understanding of Page Object Model and test maintainability strategies.
API Testing
Proficient in API testing using RestAssured, Postman, or similar tools.
Experience validating complex API workflows and backend integrations.
Job Title : Lead AI QA Automation Engineer
Location : Charlotte, NC 28202 (Onsite)
Duration : 12 Months
Job Details:
Job Summary
We are seeking a Senior / Lead AI QA Automation Engineer to drive the next generation of AI-powered test automation using Generative AI and Model Context Protocol (MCP) based solutions. This role will focus on building intelligent systems that ingest user stories, acceptance criteria, and test context from tools such as JIRA, Confluence, APIs, and code repositories, and automatically generate, execute, and maintain UI and API automation.
The ideal candidate will design context-aware, self-healing automation ecosystems using LLMs and MCP to reduce manual effort, improve reliability, and enable true shift-left quality engineering across agile teams.
Key Responsibilities
AI & MCP-Based Test Generation
Design and implement MCP-based AI solutions that provide LLMs structured access to:
User stories and acceptance criteria (JIRA/Confluence) Existing test assets and automation frameworks Application metadata, APIs, and UI locators Use LLMs (e.g., GPT-4, Claude) with MCP to automatically generate:
BDD test scenarios (Gherkin)
Executable UI and API automation scripts Test data and edge-case coverage Ensure generated tests remain context-aware, explainable, and traceable to requirements.
Intelligent Automation Framework Development
Build and enhance AI-driven automation frameworks incorporating:
MCP-based context retrieval for dynamic test generation Self-healing locators and adaptive test flows Automatic test refactoring when application or requirements change Establish standards for scalable, reusable, and maintainable automation.
Shift-Left & Agile Quality Enablement
Enable test creation during story grooming and development sprints using AI-assisted workflows.
Provide immediate feedback to developers via MCP-powered test execution and analysis.
Collaborate closely with product owners, developers, and platform teams.
AI Application & Model Validation
Validate AI-enabled features and systems, including:
Prompt behavior and response quality
MCP context accuracy and relevance
RAG pipelines and tool-based grounding
Non-deterministic outputs and hallucination risks Define validation strategies, scoring thresholds, and acceptance criteria for AI-driven functionality.
UI & API Automation
Develop robust UI automation using Playwright (preferred), Selenium, or Cypress.
Create comprehensive API automation for RESTful services and backend integrations.
Ensure consistency between AI-generated tests and hand-crafted regression suites.
Flaky Test Detection & Optimization
Leverage AI and MCP context to:
Identify flaky tests and root causes
Correlate failures with application, environment, or data changes Automatically recommend or implement fixes Improve overall test suite stability and reliability.
Required Skills & Qualifications:
AI, MCP & Generative Automation
1 years of experience building AI-driven test automation solutions.
Hands-on experience using LLMs with structured context, including:
Model Context Protocol (MCP) or equivalent tool-based/contextual grounding approaches OpenAI APIs, Claude, LangChain, or similar orchestration frameworks MCP Architecture & Tooling:
Experience defining MCP servers, tools, and context sources to safely expose enterprise data to LLMs for test automation use cases.
Prompt Engineering & Context Design:
Ability to design prompts and MCP context boundaries that produce high-quality, deterministic, and auditable test outputs.
AI Output Analysis:
Experience analyzing non-deterministic AI outputs and defining scoring, confidence thresholds, and validation rules.
Desired Skills & Experience:
Automation & Programming
Strong expertise in Playwright (preferred), Selenium, or Cypress.
Proficiency in Python or TypeScript/JavaScript.
Solid knowledge of automation design patterns and test architecture.
BDD & Test Engineering
Extensive experience with BDD frameworks (Cucumber/Gherkin).
Strong understanding of Page Object Model and test maintainability strategies.
API Testing
Proficient in API testing using RestAssured, Postman, or similar tools.
Experience validating complex API workflows and backend integrations.