• Professional responsible for ensuring the quality of software deliveries, acting critically and analytically to validate features before they are released to end users. • Must have strong attention to detail, the ability to identify defects and propose improvements, and work collaboratively with agile teams. • Planning and execution of functional and automated tests • Creation of test scenarios and test cases based on requirements • Identification, logging and tracking of bugs • Validation of deliverables produced by the development team • Participation in agile ceremonies (daily, planning, review, retrospective) • Creation and maintenance of automated tests • Support in defining acceptance and quality criteria • Reporting results and analyzing the quality of deliverables

Role Description As a Head of QA at Smartcat, your mission is to be a company-wide centre of QA excellence, elevating our product quality to match that of top-tier tech companies. You will innovate testing strategies, enhance cross-department collaboration, and lead the QA team towards excellence, ensuring Smartcat exceeds customer expectations in reliability and user experience. Outcomes - Build a quality management system to reduce the number of production bugs by 50%. - Collaborate with Engineering Directors to create an effective automated testing process, including end-to-end, unit, and API tests. - Develop a testing process with developers’ involvement to integrate testing into the development process. - Define quality metrics and test strategies to develop testing procedures. - Continuously implement AI-based QA approach. Qualifications - Have at least 10+ years of experience as a QA engineer, with 5+ years as QA lead of 5+ people. - Established testing processes and supported them. - Know and value standards of quality, software testing methodologies, and test design techniques. - Have 5+ years of practical experience in test process automation with REST API and UI on any high-level programming language (C# is preferable). - Know why and how to bring testing outside the boundaries of the QA team. - Have experience with Selenium Webdriver, Git, and Allure. Knowledge of Docker and DevOps practices will be a considerable advantage. - Ready to work in a dynamic atmosphere of a startup and bring something new to the table. - Have no fear in making decisions and can provide results in set time frames. Requirements - Experience in hiring team members. - Capability to motivate, teach, and help team members reach personal goals. - Practical experience in integrating automating testing processes. Benefits - Fully remote team. - Global team of 180+ enthusiastic people spread across 30 countries. - Innovating the $50 billion language translation industry. - High impact role enabling innovation and inclusion in organizations. - Opportunity to transition from a post-Series B startup to a company exceeding $100M in ARR and $1B in valuation. Company Description Smartcat is building the future of work, where human expertise meets digital teammates to drive productivity gains for the world’s leading enterprises. Our platform combines generative AI, human-in-the-loop workflows, and a living Enterprise Skill Graph that continuously learns and improves. - Founded in 2016 to help global enterprises create and manage their multilingual content. - Trusted by more than 1,000 global companies including 25% of the Fortune 500. - Backed by leading VC firms focusing on SaaS, marketplaces, and AI. - Growing at 150% YoY, providing a unique combination of a hyper-growth environment with downside protection.

• Watch recorded student conversations and compare them to their corresponding transcripts • Identify and document transcription errors, including: missing or dropped words, incorrect phrasing, speaker misattribution, moments where meaning is unclear or distorted • Tag and categorize types of errors to help us understand patterns • Help define what “good enough” transcript quality looks like for our use case

• Build and ship production-grade, automated validation frameworks, test harnesses, and evaluation pipelines across the AI lifecycle (design → deploy). • Design and evolve an AI testing platform integrated with Databricks and MLflow, enabling repeatable testing, traceability, and auditability. • Create large-scale, scenario-based test suites (hundreds to thousands of cases) to validate agentic workflows end-to-end, including edge cases, long-tail scenarios, and failure modes. • Validate orchestration behavior (tool use, memory, decision logic) and stress-test non-deterministic system behavior before production. • Embed quality by design: define system contracts, guardrails, and safe-degradation patterns at key boundaries. • Define measurable quality signals for LLM systems (grounding, hallucinations, relevance, latency, cost) and integrate them into CI/CD pipelines as automated quality gates. • Ensure AI validation runs automatically on model, prompt, and code changes—enabling continuous quality enforcement. • Build reusable libraries and components so teams can adopt consistent AI quality practices quickly. • Own aspects of AI release readiness, including defining go/no-go criteria based on measurable quality thresholds. • Partner with AI, platform, security, and delivery teams to translate mission needs into clear quality criteria, tradeoffs, and confidence levels.