Senior AI SDET Engineer

Octaura•New York, NY

2d•$150,000 - $180,000•Onsite

About The Position

Ocaura is a technology company transforming how some of the world’s largest, least digitized markets operate. In loans and CLOs, trillions of dollars still move through phones, emails, and PDFs because the right infrastructure hasn’t existed — until now. We’re applying AI, real-time data, and modern software design to asset classes long overlooked by fintech. Our platforms turn fragmented information into intelligence, manual workflows into automation, and legacy conventions into scalable market infrastructure. You’ll join a high-impact, collaborative team building the systems these markets need to become more transparent, efficient, and connected. A performance-first senior SDET engineering role for a hands-on contributor who can own performance testing strategy, contribute significantly to automation framework architecture, and help advance AI engineering practices within the SDET organization. We are looking for a highly technical SDET engineer to join our Quality Engineering organization and be a part of performance engineering, automation architecture, and test infrastructure development team. This is a hands-on engineering position for someone who enjoys solving complex technical problems, designing scalable testing solutions, and improving engineering productivity through modern software development practices and AI-assisted workflows. The ideal candidate must have performance testing expertise, strong software engineering fundamentals, and the ability to contribute to the evolution of automation frameworks and engineering practices across the organization. This role is expected to be a senior technical contributor within the SDET organization, helping shape testing strategy, mentor team members, and drive engineering excellence. The primary focus for this role is agentic development practices, Performance engineering strategy, workload modeling, bottleneck analysis, capacity testing, and scalable performance validation. As an IC, you will be heavily involved in automation framework architecture, TypeScript/Playwright platform work, code reviews, mentoring, and AI-assisted engineering practices. This is not just an automation scripting role.

Requirements

7+ years of experience in SDET/QA Automation, Performance Engineering, or a related field. Exceptional candidates with less traditional experience may be considered if they demonstrate strong technical depth.
Experience working within modern software development teams using Git-based workflows and CI/CD practices.
Strong experience with load testing, stress testing, endurance testing, scalability testing, and capacity-oriented validation.
Strong ability to analyze performance bottlenecks and perform root-cause investigation across application, database, infrastructure, and architectural layers.
Ability to interpret performance metrics, identify trends, and translate findings into actionable engineering recommendations.
Hands-on experience with one or more performance testing platforms such as k6, Artillery, Gatling, JMeter, Locust, or equivalent tools.
Strong understanding of Object-Oriented Design, SOLID principles, design patterns, clean code, refactoring, and software architecture.
Strong understanding of unit testing, integration testing, API testing, and testability-focused design.
Strong understanding of relational databases and SQL.
Ability to evaluate trade-offs, design reusable components, and make sound architectural decisions.
Strong development experience with TypeScript / JavaScript.
Strongly preferred experience with Playwright and the modern TypeScript ecosystem.
Experience with automation framework development, API testing, end-to-end testing, and CI/CD integration.
Good to have knowledge with Java, Python, or C#.

Responsibilities

Actively participate in performance testing initiatives across multiple applications and services.
Design and execute load, stress, endurance, scalability, spike, resilience, and capacity tests.
Define realistic workload models, performance validation strategies, baselines, and success criteria.
Analyze applications, databases, infrastructure, and architectural bottlenecks.
Work closely with software engineers and architects to improve system performance and scalability.
Establish performance testing standards, best practices, and reporting methodologies.
Drive integration of performance testing into CI/CD pipelines and regular engineering workflows.
Define and track performance KPIs, quality metrics, and actionable performance signals.
Mentor engineers on performance testing methodology, interpretation of results, and common anti-patterns.
Design, develop, and maintain automation framework components and shared test infrastructure.
Improve framework scalability, maintainability, readability, and developer experience.
Create reusable libraries, utilities, fixtures, helpers, and common engineering patterns.
Participate in framework architecture decisions and provide meaningful code review feedback.
Help reduce technical debt through refactoring, modernization, and stronger engineering standards.
Support the team in building reliable, concise, and maintainable test automation across UI, API, integration, and end-to-end layers.
Write clean, maintainable, and production-quality code.
Participate in technical design and architecture discussions.
Review pull requests and provide constructive feedback on design, maintainability, testability, and long-term architecture.
Apply modern engineering practices, including unit testing, integration testing, refactoring, and clean code principles.
Promote testability, maintainability, observability, and engineering excellence across the organization.
Mentor SDETs and collaborate with developers to improve quality earlier in the development of lifecycles.
Use AI tools to improve development and testing efficiency.
Leverage AI for code generation, refactoring, code review support, debugging, documentation, and test generation.
Evaluate emerging AI technologies and practical engineering applications.
Help establish pragmatic AI engineering standards, prompts, workflows, and best practices within the team.