About this role
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.
Requirements:
- 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.
Benefits:
- 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.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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