Software Engineering Manager, Performance and Quality Frameworks

Description

This is a remote role open to US-based candidates. Candidates must be US citizens, a requirement tied to FedRAMP standards. The interview process includes an in-person interview.

The company builds identity security software. Its platform covers both human and non-human identities, including AI agents, and is used by large, complex organizations to run identity security at scale.

The team builds and scales the core infrastructure, performance engineering platforms, and shared functional testing frameworks that all engineering groups at the company use. Its focus is developer productivity, reliability at enterprise scale, and letting engineering squads ship quality SaaS products quickly through self-service tools and AI-assisted workflows.

You will manage a group in the Engineering Quality Platform that handles performance engineering and the shared functional testing frameworks used for consistent product validation. Product teams keep ownership of tests for their own features, while your group supplies reusable tools, standards, and training.

You will work with product managers, designers, architects, quality, DevOps, product engineering, and customer-facing teams to build a strong focus on performance and quality.

Responsibilities

• Own the strategy, roadmap, reliability, documentation, adoption, and self-service experience for the shared functional testing frameworks.
• Lead the architecture, growth, and upkeep of reusable functional testing libraries, services, and capabilities.
• Drive the use of AI tools such as Cursor and Claude Code across performance scripts, test creation, framework maintenance, and result analysis, with the goal of shortening load, performance, and functional testing workflows.
• Work through hard scalability and reliability problems and make sound technical decisions with your team.
• Within your first 30 days, learn the product, stack, and top five initiatives, get to know your team, measure current adoption, flakiness, test-development time, coverage, and support load, find where AI can help, and interview stakeholders to set the line between shared framework ownership and product-team test ownership.
• Within 90 days, run AI pilots with measurable gains, set a prioritized roadmap for framework growth, reliability, documentation, and self-service, and hold regular syncs with stakeholders while planning two to three years ahead.
• Within six months, have the team using AI to find performance bottlenecks, reduce technical debt, and produce useful findings; expand shared frameworks to priority use cases; and keep shipping and defect fixing in balance.
• Within one year, have AI tools built into daily performance and framework work, size and skill the team to match the roadmap, use data to measure impact, coach engineers toward expertise, and help product teams own their feature tests through self-service.

Requirements

• Must be a US citizen, as required under FedRAMP standards.
• At least 2 years of engineering leadership experience.
• At least 8 years of hands-on experience as a performance or software engineer.
• A bachelor's degree in a related field, or equivalent work experience.
• Proven experience building, extending, and maintaining shared functional testing frameworks, libraries, or services used by several product teams.
• Proven use of AI coding tools such as Cursor and Claude Code to write, debug, maintain, and improve complex code.
• Ability to choose the right AI model or agent for an engineering problem, with a focus on team efficiency and test coverage.
• Ability to track and improve how the portfolio uses AI, and to cut engineering and test-development cycle time for features that involve performance work or shared frameworks.
• Ability to build relationships with outside teams that encourage self-service, drive framework adoption, and secure dedicated time for hands-on load, stress, and performance testing of end-to-end functionality.
• Experience using adoption, flakiness, cycle time, coverage, and support load data to set priorities.
• Strong interest in high-performance, high-load SaaS, reliable test infrastructure, and testable, performant design.
• Experience designing, building, and running distributed, scalable, highly available systems in a public cloud, preferably AWS.
• Deep knowledge of microservices, containerized CI/CD with Docker and Kubernetes, and agile methods.
• Clear technical writing that people can read easily and that LLMs can also parse well.
• Effective leadership, mentoring, and project management skills.
• Engineers here use AI tools as a daily part of their work. You will use them to speed up delivery, widen your scope, and raise quality, and you will review and validate all AI-generated code you ship. Prompting, agentic workflows, and human review of AI output are baseline expectations.
• Relevant technology: Cursor, Claude Code, Python AI and ML libraries such as scikit-learn, pandas, and numpy, PyTorch, and LLMs and foundation models on Bedrock, Vertex AI, or similar platforms.

Conditions

Remote, US-based. An in-person interview is required.

US citizenship is required under FedRAMP standards.

Base salary for US-based employees is estimated at $140,500 to $236,826 USD. Pay is set within a broad range based on skills, experience, market, location, and internal peer equity. Salaries elsewhere are competitive for each location.

The role may be eligible for the corporate bonus plan or a role-specific commission, and possibly for equity.

Benefits and pay vary by work location and employment type.

The company is an equal opportunity employer.

Benefits

• Competitive pay.
• Flexible vacation policy and 8 paid holidays each year, plus sick leave.
• Paid parental leave.
• Medical, dental, and vision insurance, with premium options.
• Short-term and long-term disability coverage.
• Life insurance and AD&D, with supplemental life coverage for employees, spouses, and children.
• Flexible spending accounts for healthcare and dependent care, plus a limited purpose FSA.
• 401(k) with company matching.
• Health Savings Account with an employer contribution.
• Employee Assistance Program and care counselors.
• Optional coverage for legal help, critical illness, accident, hospital indemnity, and pets.
• Career growth opportunities.