Senior Software Development Engineer in Test

Overview

Senior Software Development Engineer in Test I (Senior SDET I) who designs and implements testing strategies and automation solutions for complex, cross-team product features, owns the automation roadmap for one or more modules, and drives AI-first quality engineering practices.

What you'll do

• Design and implement end-to-end automation frameworks and testing strategies for complex, cross-team features.
• Own the automation roadmap for one or more modules, defining goals, execution plans, and success metrics.
• Anticipate risks, identify testability gaps, and drive continuous improvements in quality and efficiency.
• Build and maintain functional, performance, resiliency, and security automation tools integrated into CI/CD pipelines.
• Design scalable test infrastructure for distributed systems, event-driven architectures, and cloud-native platforms.
• Collaborate across engineering, product, platform, and QA teams to ensure comprehensive coverage and reliable releases.
• Leverage AI-assisted automation tooling to accelerate test creation, maintenance, debugging, root-cause analysis, and release validation.
• Build AI-first automation workflows using LLM-powered tooling, intelligent test generation, self-healing automation, and agentic QA approaches.
• Drive innovation in autonomous quality engineering systems, including AI-assisted CI/CD validation, failure triaging, and predictive quality analysis.
• Champion modern quality engineering practices including observability-driven testing, production validation, synthetic monitoring, and intelligent automation standards.
• Provide technical mentorship to SDETs and engineers, elevating automation design, AI-assisted engineering practices, and code quality across teams.

What you'll need

• At least 6+ years of experience in SDET contributions, automation engineering, and quality tooling.
• Passion for delivering high-quality, reliable products through automation and intelligent testing strategies for both frontend and backend systems.
• Advanced proficiency in testing methodologies, automation frameworks, debugging techniques, and distributed system validation.
• Experience building and maintaining test infrastructure across multiple platforms and services.
• Strong command over algorithms, data structures, databases, and scripting languages (SQL, Python, JavaScript, TypeScript, or Java).
• Hands-on experience with CI/CD pipelines, performance engineering tools, observability platforms, and monitoring systems.
• Deep expertise in API and backend testing, ideally with experience in AWS and distributed systems such as Kafka, Kinesis, or event-driven architectures.
• Hands-on experience setting up performance/load/stress testing infrastructure at scale.
• Practical experience using AI-assisted development and automation tools to improve test coverage, productivity, and release confidence.
• Understanding of modern AI-first QA concepts including intelligent test generation, self-healing automation, autonomous validation workflows, and agentic QA systems.
• Comfortable evaluating and integrating emerging AI tooling into engineering and quality workflows.
• Strong systems thinking, with the ability to identify opportunities where AI can improve reliability, observability, and engineering efficiency.

Nice to have

• Experience with cloud-native QA automation architecture and tool implementation.
• Working knowledge of event-driven systems and distributed test environments.
• Familiarity with observability and monitoring tools for debugging in production.
• Experience with AI-powered testing platforms, autonomous QA agents, or LLM-assisted engineering workflows.
• Exposure to AI-assisted CI/CD validation, synthetic monitoring, chaos engineering, or intelligent release governance systems.
• Experience building scalable quality platforms for microservices and workflow orchestration systems.

Details

• Location: India.