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Readiness · Getting started
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YOUR ROLE, YOUR NEXT MOVE
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ROLE MATCH
QA Engineer at Neuroscale AI
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{"title":"QA Engineer at Neuroscale AI","requirements":["Qualifications (Required)","\u2022 Hands-on automated testing experience with Cypress, Playwright, Selenium, Pytest, Postman\/Newman, RESTAssured, or similar tools.","\u2022 Experience with A\/B testing, feature flags, analytics validation, event tracking, access control, subscription\/billing flows, or customer-specific configurations.","\u2022 Experience with performance and load testing tools such as JMeter, k6, Locust, or similar platforms."],"description":"About Neuroscale AI\nNeuroscale 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.\nNeuroscale 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.\nWe 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.\n\nRole Overview\nWe 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.\nThis 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.\nYou 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.\n\nWhat You\u2019ll Do (Key Responsibilities)\n1) Build the Quality Strategy and QA Operating System\n\u2022 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.\n\u2022 Define a company-wide QA strategy across short-term stabilization, mid-term automation, and long-term quality engineering maturity.\n\u2022 Design a scalable test architecture using test pyramid principles, shift-left testing, smoke testing, regression testing, release gates, exploratory testing, and risk-based coverage.\n\u2022 Define clear QA responsibilities between developers, QA, product, design, customer success, and release owners.\n\u2022 Establish a practical quality operating rhythm: test plans, release checklists, defect triage, severity definitions, sign-off workflows, and quality metrics.\n2) Own Product QA for ARBI and Athena\n\u2022 Validate implementation against requirements, designs, copy, acceptance criteria, user stories, and customer-specific workflows.\n\u2022 Test UI, UX, business logic, responsiveness, edge cases, error states, empty states, loading states, accessibility, and validation messages.\n\u2022 Perform exploratory, smoke, regression, and release-candidate testing before launches.\n\u2022 Validate recruiter workflows including candidate search, matching, scoring, resume parsing, outreach sequencing, scheduling, recruiter dashboards, candidate profiles, and ATS\/CRM-style workflows.\n\u2022 Validate Athena workflows including resume support, interview preparation, rubric-based feedback, candidate assistance, AI-generated recommendations, and user-facing guidance.\n3) Build and Modernize Test Automation\n\u2022 Take ownership of automated frontend, API, integration, and end-to-end test coverage using Cypress, Playwright, Pytest, Postman\/Newman, or equivalent tools.\n\u2022 Create reliable automated regression suites for critical ARBI and Athena workflows, including authentication, permissions, candidate pipelines, analytics, notifications, integrations, and admin experiences.\n\u2022 Integrate tests deeply into CI\/CD pipelines so failures are visible, actionable, and tied to release confidence.\n\u2022 Improve test reliability, execution speed, data setup, fixture management, and maintainability.\n\u2022 Introduce AI-assisted testing practices where useful, while maintaining clear human judgment and repeatable test evidence.\n4) Validate Backend, API, Data, and Workflow Reliability\n\u2022 Test robust REST APIs, Python\/FastAPI services, backend business logic, asynchronous workflows, and data-processing pipelines.\n\u2022 Validate PostgreSQL, Redis, OpenSearch, Celery, Temporal, containerized services, deployment pipelines, and AWS-hosted environments from a QA perspective.\n\u2022 Create API and integration test coverage for imports, exports, webhooks, permissions, search, scoring, candidate data, customer-specific configuration, and workflow automation.\n\u2022 Test with realistic and large-scale datasets to uncover performance, latency, search relevance, data integrity, and resilience issues.\n\u2022 Establish baseline performance, load, and reliability testing using JMeter, k6, Locust, or similar tools.\n5) QA AI, LLM, and Evaluation Workflows\n\u2022 Validate AI-assisted recruiting workflows for accuracy, consistency, explainability, hallucination risk, bias risk, prompt adherence, rubric alignment, and human-in-the-loop behavior.\n\u2022 Test AI scoring, candidate summaries, recommendations, interview feedback, resume analysis, and knowledge-retrieval experiences across normal, adversarial, and edge-case inputs.\n\u2022 Create repeatable evaluation datasets and test harnesses to measure AI quality over time.\n\u2022 Validate guardrails, fallback behavior, citations, confidence indicators, data boundaries, audit trails, and customer-specific configuration.\n\u2022 Partner with product and engineering to define what \u201cgood\u201d means for AI-generated outputs and how release readiness should be measured.\n6) Own Release Readiness and Quality Visibility\n\u2022 Create clear, structured, reproducible bug reports with screenshots\/videos, environment details, severity, expected behavior, actual behavior, impact, and reproduction steps.\n\u2022 Retest fixed issues, validate root-cause resolution, and prevent regressions.\n\u2022 Communicate QA status clearly before release: passed, failed, blocked, passed with known issues, or requires founder\/product decision.\n\u2022 Build dashboards and reporting for test coverage, defect trends, regression health, release risk, performance baselines, and customer-impacting quality issues.\n\u2022 Help developers produce testable, high-quality code by establishing testing standards, review practices, and shared quality expectations.\n\nWhat Success Looks Like (First 6\u201312 Months)\n\u2022 A clear QA audit, quality strategy, and implementation roadmap are delivered and accepted by engineering and product leadership.\n\u2022 A comprehensive ARBI and Athena test case portfolio exists across critical user journeys, backend services, data workflows, AI behavior, integrations, and release gates.\n\u2022 Automated test coverage increases meaningfully across the highest-risk frontend, API, integration, and regression areas.\n\u2022 CI\/CD quality gates are established so test results directly inform release decisions.\n\u2022 Baseline performance, load, security-oriented, and resilience testing practices are introduced for critical workflows.\n\u2022 Release readiness becomes transparent, repeatable, and trusted by founders, engineering, product, customer success, and customers.\n\u2022 You become the central authority for product quality and a mentor to developers on testing best practices.\n\nQualifications (Required)\n\u2022 Experience in Quality Assurance, Quality Engineering, Software Test Engineering, or a related product-quality role.\n\u2022 Experience testing SaaS web products, B2B platforms, workflow systems, data-heavy applications, or AI-enabled products.\n\u2022 Strong manual QA skills: exploratory testing, edge-case discovery, cross-browser validation, responsive web testing, clear bug reporting, and release sign-off.\n\u2022 Hands-on automated testing experience with Cypress, Playwright, Selenium, Pytest, Postman\/Newman, RESTAssured, or similar tools.\n\u2022 Strong backend engineering fluency, especially with Python, FastAPI, REST APIs, PostgreSQL, Redis, OpenSearch, Celery, Temporal, containers, AWS services, and deployment pipelines.\n\u2022 Experience validating large-scale datasets, data pipelines, integrations, asynchronous workflows, search\/indexing behavior, and workflow automation.\n\u2022 Experience integrating automated tests into CI\/CD pipelines and improving reliability, speed, observability, and developer feedback loops.\n\u2022 Strong systems thinking, sound quality architecture judgment, and the ability to move from ambiguity to an executable QA roadmap.\n\u2022 Ability to operate in startup-style environments with high ownership, speed, accountability, and mentoring responsibility.\n\u2022 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.\n\nPreferred Qualifications\n\u2022 Prior experience as a Staff QA Engineer, Lead QA Engineer, Quality Engineering Lead, SDET Lead, Founding QA Engineer, or QA Architect.\n\u2022 Experience testing AI\/LLM products, evaluation workflows, RAG systems, AI copilots, agentic workflows, or human-in-the-loop decision systems.\n\u2022 Experience in HR tech, recruiting platforms, ATS\/CRM systems, career services, assessment platforms, or workforce development products.\n\u2022 Experience with A\/B testing, feature flags, analytics validation, event tracking, access control, subscription\/billing flows, or customer-specific configurations.\n\u2022 Experience with performance and load testing tools such as JMeter, k6, Locust, or similar platforms.\n\u2022 Familiarity with security, privacy, accessibility, SOC 2-style controls, federal deployment expectations, or auditability requirements.\n\u2022 Comfort working directly with founders, customers, customer success, and implementation teams to translate real-world feedback into quality improvements.\n\nCurrent \/ Target Tech Environment\n\u2022 Frontend: ReactJS \/ modern web application interfaces.\n\u2022 Backend: Python, FastAPI, REST APIs, PostgreSQL, Redis, OpenSearch, Celery, Temporal, and asynchronous workflow services.\n\u2022 Infrastructure: AWS, Docker, containers, CI\/CD pipelines, observability tooling, and production SaaS deployment practices.\n\u2022 Testing: Cypress \/ Playwright-style E2E testing, API testing, integration testing, regression suites, performance testing, and AI-assisted QA workflows.\n\nCompensation \u0026amp; Benefits\n\u2022 Base Salary: Competitive and commensurate with experience, seniority, location, and ability to own quality across the product.\n\u2022 Performance \/ Equity: Potential performance incentives and\/or equity participation based on final offer structure.\n\u2022 Benefits: Medical, dental, vision, PTO, and company-supported professional growth.\n\u2022 Learning: Support for relevant courses, conferences, certifications, technical books, and quality engineering communities.\n\u2022 Flexibility: Remote-first \/ hybrid flexibility with strong preference for Northern VA \/ DC-area alignment and occasional in-person collaboration.\n\nEqual Opportunity\nNeuroscale is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees."}0%
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- Qualifications (Required)
- • Hands-on automated testing experience with Cypress, Playwright, Selenium, Pytest, Postman/Newman, RESTAssured, or similar tools.
- • Experience with A/B testing, feature flags, analytics validation, event tracking, access control, subscription/billing flows, or customer-specific configurations.
- • Experience with performance and load testing tools such as JMeter, k6, Locust, or similar platforms.
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