Software Engineering Manager, Performance and Quality Frameworks
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Software Engineering Manager, Performance and Quality Frameworks based in United States.
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.
Accountabilities:
- Lead the team responsible for performance engineering infrastructure and shared functional testing frameworks, establishing strategy, architecture, roadmap, reliability standards, documentation, adoption, and self-service capabilities.
- Evaluate and improve the performance testing toolchain and shared testing frameworks, establishing measurable baselines for adoption, reliability, flakiness, test-development cycle time, coverage, and support burden.
- Lead the adoption of AI-assisted engineering tools to accelerate performance script development, functional framework development and maintenance, test creation, execution, optimization, and analysis.
- Identify opportunities to apply AI and agentic workflows to complex engineering and testing challenges, while ensuring strong engineering judgment, validation, and human oversight of AI-generated work.
- Develop and maintain a prioritized roadmap for framework expansion, reliability, documentation, self-service, and technical debt reduction.
- Partner with Product Managers, Designers, Architects, Quality, DevOps, Product Engineering, and Customer Facing teams to understand business and product needs and establish effective testing strategies.
- Build strong relationships with product engineering teams to encourage self-service adoption of shared frameworks and secure appropriate investment in load, stress, performance, and end-to-end testing.
- Ensure a clear division of responsibilities between shared testing framework ownership and product-team ownership of feature-specific tests.
- Use quantitative evidence, including adoption, reliability, flakiness, development cycle time, coverage, support burden, and AI-generated insights, to measure impact and guide engineering priorities.
- Lead, mentor, and develop engineers, creating an environment focused on continuous learning, technical excellence, innovation, and effective collaboration.
- Ensure the team balances delivery of new capabilities with defect resolution, reliability improvements, and sustainable technical development.
- Establish a forward-looking strategy for scaling engineering and shared testing capabilities over a two- to three-year horizon.
- Build and maintain technical documentation that is accessible to engineers while also being structured for effective consumption by modern AI and large language model systems.
- Attract and retain engineers who are motivated by high-performance software, testing platforms, and AI-assisted engineering.
- 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.
- Remote-first position based in the United States.
- Base salary range of $140,500–$236,826 USD, with compensation determined based on factors including knowledge, skills, experience, market conditions, location, and internal equity.
- Potential eligibility for a corporate bonus plan and/or equity participation, depending on role and applicable programs.
- Medical, dental, and vision insurance.
- Short-term and long-term disability coverage.
- Life insurance and Accidental Death & Dismemberment (AD&D) coverage.
- Supplemental life insurance options for employees, spouses, and children.
- Flexible Spending Accounts, including healthcare and dependent care options.
- Health Savings Account with employer contribution.
- 401(k) savings and investment plan with company matching.
- Flexible vacation policy, paid holidays, and sick leave.
- Paid parental leave.
- Employee Assistance Program and care counseling resources.
- Voluntary benefits including legal assistance, critical illness, accident, hospital indemnity, and pet insurance.
- Career growth opportunities and a collaborative, inclusive work environment.
- Reasonable accommodations available for qualified applicants and employees with disabilities.
Requirements:
Benefits:
Skills
As published by lever
Resume/CV, Full name, Email, Phone, Current location, Current company