Salary / Hourly Rate: $120,000 - $140,000 per year
Benefits: US Citizens Only
Role Information
Role Overview: N/A
Responsibilities: Develop and own a comprehensive QA strategy for features built for web, mobile, and messaging channels (SMS, Teams, Slack) from design through release., Design, implement, and execute test plans, automated and manual, covering functionality, performance, accessibility, usability, and security., Partner with product, design and engineering teams to embed testability early in the development process and ensure quality is built in, not bolted on., Establish and track meaningful quality metrics (e.g., defect trends, test coverage, production incidents) and use insights to drive continuous improvement., Lead tool-selection, framework evolution, and process innovation to optimize testing workflows, increase velocity without sacrificing quality., Champion quality across the product — bug discovery, root-cause analysis, red-teaming AI features, synthetic data tests — and ensure our platform delivers at enterprise scale.
Qualifications: 3+ years of QA or software engineering experience, ideally in a startup or early stage company where you helped build and scale products for enterprise use., Demonstrated experience testing modern web, mobile, and/or messaging-based applications — you understand integrations, front-end/back-end interaction, and enterprise requirements., Skilled in both manual and automated testing: you know how to write test scripts, select appropriate tools, and manage test automation strategy., Strong analytical mindset: you use data and observability to identify root causes, measure impact of quality improvements, and drive decision-making., Excellent communication and collaboration skills: you work across functions (product, design, engineering, customer success) to deliver a high-quality user experience., Bonus: Experience testing or validating AI-first features, including red-teaming, synthetic data, evaluation pipelines and emerging QA approaches for AI., Bonus: Familiarity with accessibility (a11y), performance testing, and enterprise deployment environments.
Minimum Requirements: 3 + years of experience in QA or software engineering, ideally within a startup or high-growth environment.,Proven track record testing modern web, mobile or messaging applications (integrations, performance, accessibility, security).,Strong proficiency in both manual and automated testing techniques and relevant tools/frameworks.,Excellent communication skills: able to collaborate with product, design and engineering, and articulate quality concerns to technical and non-technical stakeholders.,Must be authorized to work in the U.S. without future visa sponsorship.
Screening Questions: (Optional Video). This step is completely optional. If you’d like, record a short 2–3 minute video introducing yourself and your experience — or share a recording of your interview with the recruiter if that’s easier. You can upload the link via Loom or Google Drive. This just helps us get to know you better, but there’s no pressure if you’d prefer to skip it.,(Optional Portfolio / GitHub) If available, please share a link to your GitHub, portfolio, or any recent projects you’ve worked on. This is entirely optional but helps provide more context about your work.,What excites you most about Arist and why are you leaving your current opportunity for this one?
Company Information
About Company: N/A
Culture: N/A
Additional Information
Interview Process: • Initial Call (30 minutes) – A recruiter or hiring manager will have a conversation with you to review your background, motivations, and fit for the role.• Technical Deep Dive (60-90 minutes) – You’ll meet with senior engineers to discuss real-world technical problems: system-level diagnostics, product architecture, and integration scenarios.• Practical Exercise / Case Study – A take-home or live assignment focused on troubleshooting a SaaS system, diagnosing an issue, and proposing resolution steps.• Final Round (60 minutes) – Interviews with cross-functional team members and founders to assess collaboration style, communication, ownership, and alignment with mission.
Day to day: You’ll lead the charge in maintaining and elevating quality across a high-impact, AI-driven learning platform used by enterprise clients. On any given day you might be designing test frameworks, reviewing integration flows between messaging and backend services, collaborating with product and design to embed testability early, and analyzing production metrics to identify edge-cases and opportunities for improvement. Your work will directly support teams worldwide and ensure the system performs reliably at scale.
Team: You’ll join a compact, highly technical team that reports directly into the engineering leadership and works closely with product and design. The role offers significant ownership — you’ll shape the testing roadmap, influence quality standards, and help define how QA operates in a fast-growing company. Collaboration is essential: you’ll partner across functions to ensure product integrity and user experience excellence.
Growth: Take ownership of end-to-end quality delivery across multiple product modules., Influence product direction by communicating insights from user metrics, performance trends, and QA findings., Mentor and build best practices for newer QA and engineering team members., Build a reputation for shipping reliable, enterprise-grade systems, positioning you for future leadership roles in quality engineering, reliability, or product.
Ideal Candidate Profile: Innovative Builder — Designs and deploys sophisticated AI workflows that solve complex, real-world enterprise challenges., Forward Deployed Mindset — Thrives on working directly with customers, gathering feedback, and iterating rapidly to solve problems in the field., Product-Minded Communicator — Excels at collaborating with users, clients, and cross-functional teams to shape solutions and drive adoption., Technically Excellent — Brings strong expertise in Rails (REST APIs, PostgreSQL, ActiveRecord, RSpec) and hands-on experience deploying scalable AI systems using modern frameworks and infrastructure., Collaborative and Fast-Moving — Thrives in ambiguity, learns new frameworks (LangChain, LlamaIndex, etc.) quickly, and delivers results at startup speed. Works seamlessly with founders, engineers, and product teams to iterate rapidly.
