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Octaura is transforming how large, traditionally non-digital markets operate, specifically in loans and CLOs where trillions of dollars still move through legacy channels. The company applies AI, real-time data, and modern software design to create scalable market infrastructure.
This is a hands-on senior SDET role focused on performance testing strategy, automation framework architecture, and advancing AI engineering practices. You'll own performance engineering initiatives across multiple applications and services, designing and executing load, stress, endurance, scalability, spike, resilience, and capacity tests. Key responsibilities include defining realistic workload models, analyzing application and infrastructure bottlenecks, establishing performance testing standards, and driving integration of performance testing into CI/CD pipelines.
On the automation side, you'll design and maintain automation framework components, improve framework scalability and maintainability, create reusable libraries and utilities, and participate in architecture decisions. You'll write production-quality code, conduct meaningful code reviews, and help reduce technical debt through refactoring and modernization.
A significant aspect of this role involves leveraging AI tools to improve development and testing efficiency—using AI for code generation, refactoring, code review support, debugging, and test generation. You'll help establish pragmatic AI engineering standards and workflows within the team.
You'll mentor other SDETs and collaborate with developers to improve quality earlier in development lifecycles. This is not an automation scripting role; it requires strong software engineering fundamentals, performance testing expertise, and the ability to shape testing strategy across the organization.
Required: 7+ years in SDET/QA Automation, Performance Engineering, or related field. Strong experience with load testing tools (k6, Artillery, Gatling, JMeter, Locust, or equivalent). Deep understanding of OOP, SOLID principles, design patterns, clean code, and software architecture. Proficiency with relational databases and SQL. Experience with modern Git-based workflows and CI/CD practices. Strong ability to analyze performance bottlenecks and translate findings into actionable recommendations.
