Job Description:
About Streamline:
Streamline s mission is to build innovative technological solutions that empower people who improve behavioral health and quality of life of those in need. We are a high growth technology company that delivers web-based software for healthcare organizations to provide and coordinate all service delivery processes. Streamline has been offering software in the behavioral health marketplace since 2003. Streamline has built and maintains systems for some of the premier behavioral health organizations in United States of America, using the latest web-based technology.
Role Overview
This role requires a blend of technical depth, AI solution development skills, and architectural vision to drive innovation in Quality Assurance and accelerate intelligent test automation.
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We are seeking an AI QA Architect with a strong background in Quality Engineering and hands-on expertise in applying Artificial Intelligence (AI) and Generative AI (GenAI) across testing workflows.
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The ideal candidate will architect, design, and implement AI-driven QA frameworks , build agent-based GenAI applications , and integrate intelligent automation solutions into enterprise QA ecosystems.
Key Responsibilities
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AI-Driven QA Strategy & Architecture
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Design and implement AI-powered QA frameworks integrating capabilities such as self-healing automation, intelligent defect prediction, test case generation, and root cause analysis.
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Define and execute the AI enablement roadmap for QA practices, leveraging LLMs, ML models, and automation accelerators.
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GenAI Application Development
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Develop Agent-based GenAI applications using frameworks such as LangChain, LlamaIndex, or Semantic Kernel .
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Enable multi-agent collaboration for test generation, failure triage, and defect clustering.
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AI Application Integration & Automation
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Build and integrate GenAI applications with GitHub Copilot , CI/CD pipelines, and test automation frameworks.
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Implement AI-based copilots to assist test engineers with code suggestions, scenario design, and defect classification.
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Host and deploy AI applications on cloud (Azure/AWS/GCP) or on-premise intranet environments , ensuring security and compliance.
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Hands-On Development & Implementation
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Develop AI/ML components using Python, JavaScript, or Java , integrating APIs from OpenAI, Gemini, Claude, or Azure OpenAI Service .
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Create and fine-tune LLM prompts and workflows for test artifact generation, requirement understanding, and automation script synthesis .
Required Skills & Experience
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Core QA Expertise:
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10+ years of QA experience, with strong knowledge of automation frameworks, performance testing, and CI/CD integration .
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Proven experience architecting or scaling test automation frameworks (Selenium, Playwright, Cypress, etc.).
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AI & GenAI Skills:
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Hands-on experience in AI-based QA solutions self-healing, test generation, or intelligent analytics.
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Experience developing Agent-based GenAI apps using LangChain, LlamaIndex, AutoGen, or CrewAI .
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Strong understanding of prompt engineering, RAG workflows, and LLM model tuning .
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Experience integrating with GitHub Copilot or other AI developer assistants.
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Programming & Tools:
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Proficiency in Python (preferred), Java , or JavaScript for AI and automation development.
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Familiarity with OpenAI, Hugging Face, Gemini, or Anthropic APIs .
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Knowledge of Azure, AWS, or GCP for AI service deployment and monitoring.
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Experience using Docker, Kubernetes, and REST APIs for app deployment.
Preferred Qualifications
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Experience implementing AI-driven QA accelerators or GenAI copilots within enterprise testing environments.
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Knowledge of security, compliance, and governance for AI-enabled testing workflows.
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Contributions to open-source AI or QA projects will be an added advantage.
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Certifications in AI/ML, Cloud (Azure/AWS), or Advanced Test Automation preferred.
