Software Engineering Manager, Performance and Quality Frameworks

This role leads a highly technical engineering team responsible for performance engineering and shared functional testing frameworks used across a SaaS engineering organization. You will shape the strategy, architecture, roadmap, reliability, and adoption of reusable testing capabilities that help product teams deliver scalable, high-quality software. The position combines engineering leadership with hands-on technical direction across performance, scalability, reliability, and test automation. A major focus will be using AI-assisted engineering tools to accelerate development, testing, maintenance, analysis, and optimization. You will partner with Product, Architecture, Quality, DevOps, Engineering, and customer-facing teams to establish strong self-service testing practices. The role offers significant scope to influence engineering productivity, technical quality, and the evolution of testing capabilities at enterprise scale.

• At least 2 years of experience in an engineering leadership role and 8+ years of hands-on experience as a performance engineer or software engineer.
• Bachelor’s degree in a related field or equivalent professional experience.
• Proven experience architecting, expanding, and maintaining shared functional testing frameworks, libraries, or services used by multiple product teams.
• Demonstrated experience architecting, developing, and supporting highly distributed, scalable, and highly available systems in a public cloud environment, preferably AWS.
• Deep knowledge of microservice architectures, containerized CI/CD environments, Docker, Kubernetes, and agile development methodologies.
• Proven hands-on experience with AI-assisted development tools such as Cursor and Claude Code, including using them to write, debug, maintain, and optimize complex software.
• Ability to select appropriate AI models and agents for specific engineering problems and measure their impact on engineering productivity, test coverage, and development cycle time.
• Strong understanding of performance engineering, high-load SaaS systems, scalable software architecture, reliable functional testing infrastructure, and principles of performant and testable design.
• Experience using quantitative evidence to identify priorities and optimize engineering processes, including framework adoption, reliability, flakiness, test-development cycle time, coverage, and support burden.
• Strong technical documentation and communication skills, including the ability to explain complex technical concepts clearly to both engineering and cross-functional audiences.
• Effective leadership, mentoring, project management, and stakeholder-management skills, with the ability to build strong relationships across teams.
• Comfort using AI development tools as a core part of daily engineering workflows, including prompting, agentic workflows, and human-in-the-loop review of AI-generated code.
• Experience with Python-based AI/ML frameworks and libraries such as scikit-learn, pandas, and NumPy is relevant, along with exposure to deep learning frameworks such as PyTorch and LLM or foundation-model platforms such as Bedrock or Vertex AI.
• Strong analytical, problem-solving, prioritization, and decision-making abilities, with a focus on measurable business and engineering outcomes.
• Must be a U.S. citizen due to FedRAMP requirements.
• Ability to interview in person as required.
• Ability to work in a remote U.S.-based role.