Staff Software Engineer

About the role

This role focuses on making testability a core platform capability so engineering teams can ship faster and more safely. You work as a builder who designs, creates, and operates testability infrastructure and practices across the organization. The position is primarily hybrid, based in Palo Alto, with flexibility for remote work in specific US time zones. You will partner closely with software engineering and platform teams to deliver internal tools that remove friction from the development lifecycle. The role demands a strong bias toward action where you prototype, iterate, and evangelize quality practices through code and documentation. You are expected to operate at the intersection of infrastructure and developer experience, ensuring testability is treated as a first-class product concern. Success is measured by how effectively your platforms enable teams to validate behavior and iterate quickly while preserving production integrity and security.

Key facts

What you'll do

Backend services and RESTful APIs are built to expose test hooks, state seeding and reset, fault injection, synthetic data generation, and environment control, enabling teams to validate behavior and iterate quickly while preserving production integrity and security.

Quality and testability metrics and SLAs are defined and tracked across services, with adoption driven through data rather than mandate, enabling continuous improvement and transparency.

Emerging AI coding and testing tools are evaluated and piloted, with org-wide patterns established for responsible AI-assisted development and testing to ensure safe and effective adoption.

You will design and implement internal developer tools that abstract complexity and provide self-service access to testability features for multiple engineering teams.

You will collaborate with product and platform stakeholders to translate testing requirements into scalable infrastructure solutions that are reliable, observable, and secure.

You will create deterministic synthetic data pipelines that enable consistent test scenarios while protecting sensitive information and maintaining data fidelity.

You will implement fault injection frameworks that allow controlled failure modes to validate resiliency and improve system robustness in production-like conditions.

You will contribute to the definition and tracking of quality SLIs and SLOs, ensuring that testability platforms provide actionable insights and drive measurable outcomes.

You will integrate testability and quality tooling into CI/CD pipelines, optimizing build and deployment workflows for speed, reliability, and developer ergonomics.

You will establish org-wide patterns for responsible AI-assisted development, guiding how LLMs and agents are used to generate tests, synthetic data, and support root-cause analysis.

Requirements

The posting states a pay range of $152000 to $185800.7+ years of software engineering experience building production backend services, with a strong track record of high-quality, maintainable code.

A Bachelor's or Master's degree in Computer Science, Computer Engineering, or a related technical discipline, or equivalent industry experience.

Demonstrated experience designing and building testability infrastructure, internal developer tools, or platform services used by other engineering teams.

Hands-on experience building and maintaining RESTful APIs and services within a microservices architecture that uses REST and gRPC.

Proven ability to design safe, access-controlled test-only interfaces or hooks into production-adjacent systems without introducing security or reliability risk.

Solid understanding of software quality methodologies and how to translate them into platform capabilities instead of manual processes.

Experience with CI/CD tooling and integrating testability and quality tooling into build and deployment pipelines.

Strong written and verbal communication skills, with experience influencing and evangelizing engineering practices across teams without direct authority.

Experience with Kubernetes and microservice architecture is a strong plus.

Genuine enthusiasm for AI-native/AI-first engineering hands-on experience using LLMs/AI agents to generate tests, synthetic data, or automate quality workflows, and a point of view on where AI should (and shouldn't) be trusted in a testability platform.

Experience using AI-assisted development tools (e.g., GitHub Copilot, Cursor, ChatGPT, or similar tools) as part of your software development workflow.

Practical notes

The position is hybrid, based in Palo Alto, with openness to candidates who can relocate or work from PT or CT time zones. Good to know

The role centers on platform thinking and testability rather than manual testing. Engineers in this role build tools and services that enable safe, fast experimentation and releases. The tech stack involves RESTful and gRPC services in a microservices environment, often supported by internal platforms. AI-native tooling is increasingly used to generate tests, synthetic data, and assist in root-cause analysis. Collaboration, communication, and influence across teams are central to driving testability practices.