Claris Backend AI Engineer In Test

We are seeking an experienced QA Engineer to join our backend team at the intersection of high-performance infrastructure and AI validation. Youll work with a Go-based microservices architecture optimized for performance paired with a Python AI service layer using large language core mission is architecting comprehensive testing and evaluation strategies for our backend platformwith a growing focus on AI-powered workflows. This means designing frameworks that validate complete flows from user request through service execution to final outcome with special attention to AI-specific concerns. Youll develop systematic testing approaches for both deterministic microservices and non-deterministic AI models. Youll build observability systems that ensure behavior remains trustworthy in need deep understanding of Cloud concepts scalable microservice architecture and modern testing practices. Equally important is understanding how AI integration impacts quality assurancehow to evaluate LLM outputs design guardrails and validate that AI recommendations integrate cleanly into backend workflows. Youll transform innovative AI research into reliable production-ready solutions that organizations depend on while maintaining the rigorous engineering rigor that makes our platform are looking for a technically excellent strategic problem solver who brings deep backend QA expertise combined with genuine curiosity about AI. The ideal candidate combines years of production quality assurance experience with foundational AI knowledge strong communication skills and ability to thrive in cross-functional collaboration. You understand that great QA isnt just finding bugsits building confidence that systems work reliably at scale. Youre eager to apply proven QA rigor to the emerging challenge of AI validation.

• 3 to 5 years of hands-on experience with production-level backend QA with expertise in testing scalable fault-tolerant SaaS applications and microservices.
• Strong experience with Go or Python programming languages and testing tools / frameworks (e.g. Ginkgo Pytest).
• Demonstrated ability to build clear comprehensive test scenarios and systematic testing strategies for complex distributed systems.
• Strong understanding of RESTful API design microservices architecture and testing modern scalable backend systems.
• Foundational knowledge of LLM / AI concepts and hands-on exposure to testing AI-powered features prompt engineering or LLM API integration in a production environment.
• Experience with testing solutions using WebSockets and webhooks. Familiar with OAuth and Single-Sign-On authentication.
• Familiar with containerization (Docker Kubernetes) and cloud environments (AWS or GCP).
• Practical experience with adversarial testing security validation or evaluating LLM outputs for safety and quality concerns.
• Knowledge of LangChain LangGraph or other AI frameworks and observability platforms for monitoring AI system behavior.
• Familiarity with implementing guardrails safety constraints or quality evaluation frameworks for AI systems.
• Experience with NoSQL databases is desired.

Key Skills

Apache Commons,Asset,Art And Craft,Concrete Pump,Accident Investigation

Employment Type : Full-Time

Experience : years

Vacancy : 1

Monthly Salary Salary : 3 - 5