Recruiter
Anastasiya Ivanenko
Roles:
QA
Must-have skills:
AWSDockerKubernetesNode.jsReactTerraformPython
Considering candidates from:
Africa, Bahrain and Brazil
Africa, Bahrain and Brazil
Work arrangement: Remote
Industry: Professional Training and Coaching
Language: English
Level: Senior or lead
Required experience: 5+ years
Size: 11 - 50 employees
Company
Pandatron is a leader in AI-driven coaching that powers change management. Their platform leverages the latest LLM/ML technologies to deliver personalized, scalable coaching experiences and collects critical business data at scale. Their vision is to develop Leadership-as-a-Service, a software that will support leaders in managing their organizations, and unlock organizational performance and business transformation through personal growth of individuals. With clients like Universal Pictures, SAP, Stora Enso, they are making coaching 10x cheaper and using it as a tool for strategy rollout and implementation, culture, and people development.
Description
Tasks:
- Provide senior-level leadership in test automation, owning the architecture and delivery of production-grade automated testing solutions that protect mission-critical AI coaching functionalities and integrations.
- Design and implement scalable automation frameworks for functional, integration, end-to-end, and regression testing across Next.js/React frontends, Node.js backends, and real-time conversational workflows.
- Develop advanced automated API testing for RESTful services, microservices, and event-driven architectures, with rigorous validation of non-deterministic LLM responses through deterministic assertions and semantic checks.
- Lead automated testing of Slack and Microsoft Teams integrations, encompassing bot logic, interactive components, webhooks, notifications, multi-turn dialogues, and real-time event processing to guarantee consistent, channel-agnostic user experiences.
- Architect automated validation suites for WebSocket-based real-time communication, event-driven systems, low-latency data pipelines, and dynamic AI response coherence in conversational contexts.
- Integrate state-of-the-art LLM quality control automation, including hallucination detection, faithfulness scoring, bias monitoring, semantic similarity assessment, and production regression testing of model deployments in partnership with the ML team.
- Champion industry-leading practices such as AI-augmented self-healing tests (e.g., via tools like Mabl, Testim, or Applitools), natural language test authoring (e.g., testRigor, KaneAI), agentic test orchestration, visual AI validation, and continuous test optimization to eliminate flakiness in AI-interactive UIs and flows.
- Establish rigorous standards for test architecture, code quality, security in testing, and observability. Mentor team members, conduct thorough test code reviews, and cultivate a culture of engineering and quality excellence.
- Collaborate cross-functionally to convert product, AI, and compliance requirements into automated, high-assurance testing solutions that support rapid, safe iteration.
- Own continuous enhancement of test coverage, pipeline efficiency, and observability, proactively implementing improvements to sustain top-tier performance amid growing Fortune 500-scale adoption.
Must-have:
- 8+ years of progressive experience in advanced test automation and quality engineering, with demonstrated leadership of sophisticated automation programs in high-impact, collaborative settings—preferably involving AI/LLM-driven, real-time, or conversational systems
- Frontend: In-depth proficiency testing modern React/Next.js applications using Playwright (preferred for cross-browser reliability and speed) or Cypress, with emphasis on dynamic, AI-interactive UIs
- Backend & API: Expert-level automation of Node.js services, scalable APIs, microservices, and event-driven architectures utilizing Jest, Mocha, or Supertest.
- DevOps & Cloud: Advanced mastery of CI/CD orchestration (GitHub Actions, GitLab CI, Jenkins), containerization (Docker, Kubernetes), AWS infrastructure provisioning and testing environments, infrastructure as code (Terraform preferred), cloud security testing practices, and pipeline observability (e.g., integration with monitoring tools like Datadog or Prometheus for test metrics and AI workload tracing).
Highly Valued / Cutting-Edge Competencies
- Modern Automation Frameworks: Hands-on experience with Playwright, Cypress, or AI-enhanced platforms featuring self-healing and agentic capabilities (e.g., Mabl, testRigor, Applitools, Testim, Katalon).
- LLM & AI Evaluation: Proven expertise with leading LLM evaluation frameworks such as DeepEval (for pytest-style testing and metrics like G-Eval, faithfulness, hallucination), RAGAS (for retrieval-augmented pipelines), Braintrust, LangSmith (LangChain ecosystem), or Arize Phoenix—enabling automated scoring of semantic relevance, bias, toxicity, and production quality gates.
- Python Proficiency: Strong command of Python for test orchestration, data-driven scenarios, ML model validation, and integration with libraries such as Pytest.
- Real-Time & Integration: Extensive automation experience with Slack/Microsoft Teams bots, webhooks, interactive elements, and WebSocket/event-driven real-time systems (including tools supporting WebSocket testing like Postman, Hoppscotch, or custom Playwright extensions).
Benefits and conditions:
- Flexible work arrangements
- Opportunity to work with cutting-edge AI technology
- Collaborative, diverse team environment
- Potential meaningful equity opportunity
- Impactful work with Fortune 500 clients
Interview process:
- Intro call with Toughbyte
- 45-min intro & behavioral interview with CTO
- Test assignment
- Team interview
- Final culture call with Hiring Manager + CEO
Questions
Have questions about this position? Try the company page or sign up to ask one.