Lead Software Development Engineer in Test (SDET)

We are seeking a Lead SDET to design, build, and scale a robotics-focused software testing organization. This role will be responsible for defining the overall test strategy, establishing robust automation frameworks, and leveraging AI-driven tools alongside AWS-based CI/CD pipelines to accelerate testing and improve product quality.

Key Responsibilities

Strategy & Technical Leadership

• Evaluate complex system requirements and define end-to-end test strategies across Hardware-in-the-Loop (HIL), Software-in-the-Loop (SIL), and simulation environments.
• Establish quality gates and testing standards across the development lifecycle.
• Drive testing architecture decisions for scalable, distributed robotics systems.

Hands-on Test Engineering

• Design, implement, and maintain scalable test frameworks from the ground up for robotics platforms.
• Debug and root-cause failures spanning software, hardware components, and sensor integrations.
• Work closely with cross-functional teams to ensure system reliability and performance in real-world conditions.

AI-Enabled Automation

• Utilize modern AI coding assistants and LLM-based tools to rapidly bootstrap test frameworks.
• Automate repetitive and boilerplate testing tasks to improve development velocity and coverage.
• Continuously explore AI-driven approaches to improve test generation and maintenance.

Cloud & CI/CD Infrastructure (AWS)

• Design and manage scalable CI/CD pipelines using AWS services such as CodePipeline, CodeBuild, and ECS.
• Build containerized testing environments using Docker for simulation and distributed test execution.
• Enable large-scale automated testing in cloud-based simulation environments.

Required Qualifications

• Strong hands-on experience in robotics software testing, including ROS/ROS2, Python, Linux, and simulation frameworks.
• Proven experience architecting test frameworks from scratch, particularly for hardware-constrained or embedded systems.
• Practical exposure to AI-powered development tools (e.g., Cursor, Copilot, or LLM-based assistants) for accelerating engineering workflows.
• Solid background in DevOps practices and building CI/CD pipelines in AWS, including containerized deployments and scalable test infrastructure.