QA Engineer

<p><strong>About <a href="https://jobicy.com/company/neuroscale-ai" target="_blank" rel="nofollow noopener">Neuroscale AI</a></strong></p> <p>Neuroscale AI is building a next-generation AI recruiting and talent intelligence platform that helps organizations turn hiring into a measurable, repeatable, and intelligent science. Our ARBI platform supports sourcing, screening, evaluation, sequencing, scheduling, recruiter workflow automation, and explainable candidate assessment for commercial enterprises, public-sector agencies, higher education, staffing organizations, and workforce-development teams.</p> <p>Neuroscale is also building Athena, an AI-powered career readiness and candidate-assistance experience that helps users improve resumes, prepare for interviews, receive rubric-based feedback, and navigate the job search process with personalized AI support.</p> <p>We are a fast-moving startup operating at the intersection of GenAI, HR technology, recruiting operations, career services, workflow automation, and enterprise AI deployment. As ARBI and Athena scale across customers, we need a senior quality leader who can make product quality measurable, automated, auditable, and trusted.</p> <p><strong>Role Overview</strong></p> <p>We are hiring a Senior QA Engineer / Quality Engineering Lead to own quality assurance, testing strategy, product validation, and release readiness across ARBI and Athena. This is a hands-on senior role for someone who can test deeply, build automated quality systems, validate AI workflows, improve developer quality practices, and become the central authority for product quality.</p> <p>This role is not limited to executing test cases. You will audit the current QA landscape, define the testing strategy, build regression and automation frameworks, validate AI behavior, pressure-test edge cases, and create the release confidence needed for a rapidly evolving SaaS platform.</p> <p>You will work closely with engineering, product, design, customer success, and founders to make sure new features, bug fixes, experiments, integrations, data workflows, and AI-driven experiences ship with clarity, reliability, auditability, accessibility, and user trust.</p> <p><strong>What You’ll Do (Key Responsibilities)</strong></p> <p><strong>1) Build the Quality Strategy and QA Operating System</strong></p> <p>• Perform a deep audit of the current QA setup across ARBI, Athena, frontend flows, backend services, APIs, data workflows, integrations, AI pipelines, and release processes.</p> <p>• Define a company-wide QA strategy across short-term stabilization, mid-term automation, and long-term quality engineering maturity.</p> <p>• Design a scalable test architecture using test pyramid principles, shift-left testing, smoke testing, regression testing, release gates, exploratory testing, and risk-based coverage.</p> <p>• Define clear QA responsibilities between developers, QA, product, design, customer success, and release owners.</p> <p>• Establish a practical quality operating rhythm: test plans, release checklists, defect triage, severity definitions, sign-off workflows, and quality metrics.</p> <p><strong>2) Own Product QA for ARBI and Athena</strong></p> <p>• Validate implementation against requirements, designs, copy, acceptance criteria, user stories, and customer-specific workflows.</p> <p>• Test UI, UX, business logic, responsiveness, edge cases, error states, empty states, loading states, accessibility, and validation messages.</p> <p>• Perform exploratory, smoke, regression, and release-candidate testing before launches.</p> <p>• Validate recruiter workflows including candidate search, matching, scoring, resume parsing, outreach sequencing, scheduling, recruiter dashboards, candidate profiles, and ATS/CRM-style workflows.</p> <p>• Validate Athena workflows including resume support, interview preparation, rubric-based feedback, candidate assistance, AI-generated recommendations, and user-facing guidance.</p> <p><strong>3) Build and Modernize Test Automation</strong></p> <p>• Take ownership of automated frontend, API, integration, and end-to-end test coverage using Cypress, Playwright, Pytest, Postman/Newman, or equivalent tools.</p> <p>• Create reliable automated regression suites for critical ARBI and Athena workflows, including authentication, permissions, candidate pipelines, analytics, notifications, integrations, and admin experiences.</p> <p>• Integrate tests deeply into CI/CD pipelines so failures are visible, actionable, and tied to release confidence.</p> <p>• Improve test reliability, execution speed, data setup, fixture management, and maintainability.</p> <p>• Introduce AI-assisted testing practices where useful, while maintaining clear human judgment and repeatable test evidence.</p> <p><strong>4) Validate Backend, API, Data, and Workflow Reliability</strong></p> <p>• Test robust REST APIs, Python/FastAPI services, backend business logic, asynchronous workflows, and data-processing pipelines.</p> <p>• Validate PostgreSQL, Redis, OpenSearch, Celery, Temporal, containerized services, deployment pipelines, and AWS-hosted environments from a QA perspective.</p> <p>• Create API and integration test coverage for imports, exports, webhooks, permissions, search, scoring, candidate data, customer-specific configuration, and workflow automation.</p> <p>• Test with realistic and large-scale datasets to uncover performance, latency, search relevance, data integrity, and resilience issues.</p> <p>• Establish baseline performance, load, and reliability testing using JMeter, k6, Locust, or similar tools.</p> <p><strong>5) QA AI, LLM, and Evaluation Workflows</strong></p> <p>• Validate AI-assisted recruiting workflows for accuracy, consistency, explainability, hallucination risk, bias risk, prompt adherence, rubric alignment, and human-in-the-loop behavior.</p> <p>• Test AI scoring, candidate summaries, recommendations, interview feedback, resume analysis, and knowledge-retrieval experiences across normal, adversarial, and edge-case inputs.</p> <p>• Create repeatable evaluation datasets and test harnesses to measure AI quality over time.</p> <p>• Validate guardrails, fallback behavior, citations, confidence indicators, data boundaries, audit trails, and customer-specific configuration.</p> <p>• Partner with product and engineering to define what “good” means for AI-generated outputs and how release readiness should be measured.</p> <p><strong>6) Own Release Readiness and Quality Visibility</strong></p> <p>• Create clear, structured, reproducible bug reports with screenshots/videos, environment details, severity, expected behavior, actual behavior, impact, and reproduction steps.</p> <p>• Retest fixed issues, validate root-cause resolution, and prevent regressions.</p> <p>• Communicate QA status clearly before release: passed, failed, blocked, passed with known issues, or requires founder/product decision.</p> <p>• Build dashboards and reporting for test coverage, defect trends, regression health, release risk, performance baselines, and customer-impacting quality issues.</p> <p>• Help developers produce testable, high-quality code by establishing testing standards, review practices, and shared quality expectations.</p> <p><strong>What Success Looks Like (First 6–12 Months)</strong></p> <p>• A clear QA audit, quality strategy, and implementation roadmap are delivered and accepted by engineering and product leadership.</p> <p>• A comprehensive ARBI and Athena test case portfolio exists across critical user journeys, backend services, data workflows, AI behavior, integrations, and release gates.</p> <p>• Automated test coverage increases meaningfully across the highest-risk frontend, API, integration, and regression areas.</p> <p>• CI/CD quality gates are established so test results directly inform release decisions.</p> <p>• Baseline performance, load, security-oriented, and resilience testing practices are introduced for critical workflows.</p> <p>• Release readiness becomes transparent, repeatable, and trusted by founders, engineering, product, customer success, and customers.</p> <p>• You become the central authority for product quality and a mentor to developers on testing best practices.</p> <p><strong>Qualifications (Required)</strong></p> <p>• Experience in Quality Assurance, Quality Engineering, Software Test Engineering, or a related product-quality role.</p> <p>• Experience testing SaaS web products, B2B platforms, workflow systems, data-heavy applications, or AI-enabled products.</p> <p>• Strong manual QA skills: exploratory testing, edge-case discovery, cross-browser validation, responsive web testing, clear bug reporting, and release sign-off.</p> <p>• Hands-on automated testing experience with Cypress, Playwright, Selenium, Pytest, Postman/Newman, RESTAssured, or similar tools.</p> <p>• Strong backend engineering fluency, especially with Python, FastAPI, REST APIs, PostgreSQL, Redis, OpenSearch, Celery, Temporal, containers, AWS services, and deployment pipelines.</p> <p>• Experience validating large-scale datasets, data pipelines, integrations, asynchronous workflows, search/indexing behavior, and workflow automation.</p> <p>• Experience integrating automated tests into CI/CD pipelines and improving reliability, speed, observability, and developer feedback loops.</p> <p>• Strong systems thinking, sound quality architecture judgment, and the ability to move from ambiguity to an executable QA roadmap.</p> <p>• Ability to operate in startup-style environments with high ownership, speed, accountability, and mentoring responsibility.</p> <p>• Ability and willingness to relocate to the Northern VA / Washington, DC area, or work closely with the team during Eastern Time business hours if remote.</p> <p><strong>Preferred Qualifications</strong></p> <p>• Prior experience as a Staff QA Engineer, Lead QA Engineer, Quality Engineering Lead, SDET Lead, Founding QA Engineer, or QA Architect.</p> <p>• Experience testing AI/LLM products, evaluation workflows, RAG systems, AI copilots, agentic workflows, or human-in-the-loop decision systems.</p> <p>• Experience in HR tech, recruiting platforms, ATS/CRM systems, career services, assessment platforms, or workforce development products.</p> <p>• Experience with A/B testing, feature flags, analytics validation, event tracking, access control, subscription/billing flows, or customer-specific configurations.</p> <p>• Experience with performance and load testing tools such as JMeter, k6, Locust, or similar platforms.</p> <p>• Familiarity with security, privacy, accessibility, SOC 2-style controls, federal deployment expectations, or auditability requirements.</p> <p>• Comfort working directly with founders, customers, customer success, and implementation teams to translate real-world feedback into quality improvements.</p> <p><strong>Current / Target Tech Environment</strong></p> <p>• <strong>Frontend:</strong> ReactJS / modern web application interfaces.</p> <p>• <strong>Backend:</strong> Python, FastAPI, REST APIs, PostgreSQL, Redis, OpenSearch, Celery, Temporal, and asynchronous workflow services.</p> <p>• <strong>Infrastructure:</strong> AWS, Docker, containers, CI/CD pipelines, observability tooling, and production SaaS deployment practices.</p> <p>• <strong>Testing:</strong> Cypress / Playwright-style E2E testing, API testing, integration testing, regression suites, performance testing, and AI-assisted QA workflows.</p> <p><strong>Compensation &amp; Benefits</strong></p> <p>• <strong>Base Salary:</strong> Competitive and commensurate with experience, seniority, location, and ability to own quality across the product.</p> <p>• <strong>Performance / Equity:</strong> Potential performance incentives and/or equity participation based on final offer structure.</p> <p>• <strong>Benefits:</strong> Medical, dental, vision, PTO, and company-supported professional growth.</p> <p>• <strong>Learning:</strong> Support for relevant courses, conferences, certifications, technical books, and quality engineering communities.</p> <p>• <strong>Flexibility:</strong> Remote-first / hybrid flexibility with strong preference for Northern VA / DC-area alignment and occasional in-person collaboration.</p> <p><strong>Equal Opportunity</strong></p> <p>Neuroscale is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.</p>

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