
501 - 1000 employees
Founded 2003
☁️ SaaS
📚 Education
🏢 Enterprise
💰 $59M Private Equity Round - Absorb LMS on 2017-09
SaaS • Education • Enterprise
Absorb Software is an AI-powered learning management system (LMS) provider that delivers a cloud-based platform for enterprise training, onboarding, compliance, upskilling, customer education, and partner enablement. Its SaaS platform includes course authoring, a large content library, reporting and analytics, integrations with HCM/CRM systems, e-commerce for selling courses, and AI agents to personalize learning and streamline administration. Absorb targets HR, L&D, compliance, customer success, and partner teams at organizations of all sizes, emphasizing scalability, security, and measurable ROI.
🔥 10 minutes ago
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501 - 1000 employees
Founded 2003
☁️ SaaS
📚 Education
🏢 Enterprise
💰 $59M Private Equity Round - Absorb LMS on 2017-09
SaaS • Education • Enterprise
Absorb Software is an AI-powered learning management system (LMS) provider that delivers a cloud-based platform for enterprise training, onboarding, compliance, upskilling, customer education, and partner enablement. Its SaaS platform includes course authoring, a large content library, reporting and analytics, integrations with HCM/CRM systems, e-commerce for selling courses, and AI agents to personalize learning and streamline administration. Absorb targets HR, L&D, compliance, customer success, and partner teams at organizations of all sizes, emphasizing scalability, security, and measurable ROI.
• Review requirements specifications and technical design documents to provide timely and meaningful feedback. • Create detailed, comprehensive, and well-structured test plans and test cases and analyze and update existing test cases. • Lead and assist more junior QA Analysts. • Estimate, prioritize, plan and coordinate testing activities. • Design, develop and execute automation scripts using open-source tools, TypeScript, Playwright, or similar automation frameworks (e.g., Cypress, Selenium). • Use AI coding assistants and agentic tools, such as Claude Code, to accelerate test authoring, maintain automation scripts, and triage defects. • Build, customize, and maintain reusable AI skills and agentic workflows that streamline repeatable QA tasks (test generation, regression checks, defect documentation). • Apply spec-driven development practices, for example the AI-Driven Development Lifecycle (AI-DLC), to translate requirements into structured specifications that guide AI-assisted test generation and validation. • Design and run evaluations ("evals") for AI-powered features to measure accuracy, relevance, hallucination rate, and other quality metrics against defined test datasets. • Apply non-deterministic testing approaches for AI/LLM-based features, using statistical thresholds, sampling, and repeated-run analysis rather than fixed pass/fail assertions. • Configure and monitor AI observability and evaluation tooling (e.g., Arize AX/Phoenix, LangSmith, or similar) to track model/agent performance, detect drift, and flag regressions in production. • Identify, record, document, track, and close bugs. • Perform thorough regression testing when bugs are resolved. • Actively transfer knowledge to other QA Team members via documentation and QA presentations, including AI-assisted testing practices and tooling. • Ad hoc duties as required.
• Proven experience in manual and automated QA testing of web applications. • Proficiency in TypeScript/JavaScript with hands-on experience in Playwright or a comparable automation framework (Cypress, Selenium, WebdriverIO). • Practical experience using AI coding assistants and agentic tools (e.g., Claude Code, GitHub Copilot) for writing, maintaining, or reviewing test automation. • Working understanding of spec-driven development methodologies (e.g., AI-DLC / AI-Driven Development Lifecycle) and how structured specifications drive AI-assisted planning, execution, and validation. • Ability to build and maintain custom AI skills, prompts, or agent workflows to streamline QA processes. • Understanding of non-deterministic testing: recognizing that AI/LLM outputs vary between runs and require different validation strategies than deterministic UI/API testing. • Experience designing evaluation ("eval") datasets and metrics (accuracy, relevance, hallucination, toxicity, latency) for AI-powered features. • Familiarity with AI observability and evaluation-monitoring platforms such as Arize (AX/Phoenix), LangSmith, or Braintrust for tracking model/agent quality in production. • Solid grounding in QA methodologies, the SDLC, and test planning/estimation. • Strong analytical, written, and verbal communication skills, with the ability to mentor junior QA Analysts.
• Fully remote-first work with flexible work arrangements 🏡 • Comprehensive Health and Wellness Benefits including retirement savings programs, eligibility for two different bonus plans, generous time off, comprehensive medical and dental benefits based on your country of location 🧘 • New Hire Equipment Allowance and monthly Flex Allowance to support your success 📦 • Endless opportunity for career growth and internal mobility 🌱 • Employee driven DE&I programs 🫶
Apply Now🔥 22 hours ago
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