AI Architect (QA Automation) - 251DSM-H Consulting • Chicago, Illinois, United States

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AI Architect (QA Automation) - 251

DSM-H Consulting

Chicago, Illinois, United States

Chicago, Illinois, United States

Über

Note: Interview will be In Person Position’s Contributions to Work Group : - We’re looking for an AI Architect to lead how our testing organization uses AI to improve quality, speed, coverage, and insight across the software delivery lifecycle. - This person will define the AI strategy for QA and testing, design AI-enabled testing solutions, guide tool selection and integration, and help teams adopt AI responsibly in day-to-day testing activities. Typical task breakdown: - Define the AI vision and architecture for the testing function. - Identify testing activities that can be improved with AI, including: test case generation, test data creation, automated test maintenance, defect prediction, root cause analysis, log and failure analysis, requirements-to-test traceability, risk-based test prioritization, intelligent regression selection - Design and implement AI-enabled frameworks for: functional testing, API testing, UI automation, performance testing, security testing support, exploratory testing augmentation - Partner with QA, developers, DevOps, product managers, and data teams to embed AI into CI/CD and quality engineering workflows. - Evaluate and recommend AI/ML, GenAI, and test automation tools. - Establish standards for AI governance, privacy, security, explainability, and responsible usage in testing. - Create architecture for integrating LLMs, test repositories, defect systems, observability tools, and CI platforms. - Define metrics to measure the effectiveness of AI in testing, such as:defect leakage, automation coverage, test execution efficiency, flaky test reduction - mean time to diagnose failures, release quality trends - Mentor QA engineers and SDETs on AI-assisted testing practices. - Lead pilots, proofs of concept, and scaled rollout of AI testing capabilities. - Ensure compliance with enterprise policies for data handling and model usage. Interaction with team : - Working with team; team consists of 20+ folks Work environment : Chicago Office: 540 W Madison Street, Chicago, IL 60661 Education & Experience Required: -
Years of experience: 8-10 yrs experience -
Degree requirement: Bachelor’s degree and 8+ years of experience
Required Technical Skills (Required) - 8+ years in software testing, QA automation, quality engineering, or test architecture. - 3+ years designing or implementing AI/ML or GenAI-based solutions in enterprise environments. - Strong understanding of: software testing methodologies, test automation frameworks - SDLC/STLC - CI/CD pipelines - quality engineering practices - Experience with AI technologies such as: machine learning models, NLP, LLMs, prompt engineering, retrieval-augmented generation concepts - AI agents/workflow automation - Hands-on experience with tools/languages such as Python, Java, JavaScript, SQL, and test tools like Selenium, Playwright, Cypress, Appium, JUnit, TestNG, PyTest, or similar. - Experience integrating with platforms such as Jira, Azure DevOps, GitHub, Jenkins, GitLab, or cloud test platforms. - Knowledge of test analytics, data pipelines, and observability/log analysis tools. - Strong architecture and design skills for scalable, secure enterprise solution (Desired) - Experience building AI copilots or assistants for QA teams. - Familiarity with vector databases, model evaluation, and MLOps/LLMOps concepts. - Experience with cloud platforms such as AWS, Azure, or GCP. - Understanding of regulated environments and compliance requirements. - Certifications in test architecture, cloud, AI/ML, or enterprise architecture. - Hands on experience with Python - development experience in AWS Cloud technology - Experience in TDD, continuous integration, code review practice is strongly desired - Experience with Apigee or other API gateways is a plus - Experience with DevOps concepts and tools (e.g., CI/CD, Jenkins, Git) - At least 2 years working on an Agile team with a solid understanding of Agile/Lean practices. - Understanding of a micro service Architecture - Experience load and performance testing - Strong documentation skills Key skills - AI strategy for testing - test architecture - quality engineering leadership - GenAI and LLM application design - automation framework design - data-driven decision making - stakeholder communication - governance and risk management - Team enablement Soft Skills (Required) - Ability to adapt quickly to a complex environment - Pro-active, flexible and creative - Very strong communication skills and the ability to collaborate with developers and business users.

Chicago, Illinois, United States

Sprachkenntnisse

English

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