Staff Test Engineer

Job Summary

We are seeking a highly skilled and experienced Backend Lead to join our AI team. As a Backend Lead, you will play a crucial role in ensuring the performance, scalability, and efficiency of our backend architecture while mentoring and leading a team of engineers. This position requires deep expertise in backend engineering, particularly in Python, and a strong understanding of building scalable and efficient systems. The ideal candidate will have a proven track record of leadership in backend development, and the ability to drive complex technical initiatives.

Responsibilities

• End-to-End Deployment Testing: Collaborate with backend engineers to deploy models via Docker/Kubernetes, and design end-to-end test strategies (on-prem and cloud) grounded in system architecture.
• CI/CD Automation: Maintain robust CI/CD pipelines and drive continuous test automation to minimize turnaround time for new releases.
• Research Distillation: Actively research state-of-the-art open-source models (e.g., Qwen3, Mistral) and apply Knowledge Distillation to create smaller, faster proprietary models.
• Monitor Improve: Continuously monitor drift, hallucination rates, and retrieval quality in production systems.
• Code Quality and Best Practices: Ensure that code adheres to best practices, including clean code principles, testing, and documentation.
• Build Agentic Systems: Implement multi-agent workflows using LangGraph to solve complex, multi-step user queries.
• Optimize for Scale: Implement Quantization and vLLM/SGLang strategies to reduce inference costs and latency in production.

Requirements

• Strong understanding of STLC, Agile and modern Quality Engineering practices, with expertise in functional, integration, API, regression, end to end, non-functional testing and compatibility testing.
• Ability to analyse requirements and system workflows, design effective test strategies, test scenarios, and risk-based test cases, and ensure comprehensive functional and non-functional coverage.
• Hands-on automation experience with Playwright/Selenium/Cypress and proficiency in Python, Java, JavaScript or TypeScript.
• Strong API and performance testing experience using tools such as Postman, REST Assured, JMeter, Gatling or k6.
• Good understanding of microservices, distributed systems, networking, databases and cloud-native architectures.
• Hands-on exposure to AWS/Azure/GCP, Docker/Kubernetes, CI/CD pipelines and Git-based workflows.
• Experience with observability, debugging and RCA using logs, metrics and monitoring tools such as Grafana, CloudWatch or ELK.
• Exposure to AI-assisted testing/development and testing of AI/LLM-based applications is an added advantage.