About the role
We’re looking for a Staff SDET to join our team. This is a broad, high-impact startup role spanning technical strategy, hands-on execution, platform development, and organizational enablement. You’ll serve as a company-wide subject matter expert for quality engineering, with a primary mandate to define, drive, and operationalize AI-enabled transformation across QA and the broader Engineering organization.
You’ll lead major cross-functional initiatives, define quality engineering roadmaps, and build scalable tooling, frameworks, and practices that help teams move faster without sacrificing quality. Your work will often cut across team boundaries, and you’ll be expected to independently identify gaps, set direction, and drive work through to adoption.
You’ll also mentor others, help evolve the QA organization toward increasingly automation/AI-first workflows, and raise the technical bar across Engineering through guilds and learning sessions. This is a staff-level individual contributor role with significant autonomy, no people management responsibility, and close partnership with the Engineering Manager of QA, Director of Quality, and Sr. Director of Infrastructure.
About the team
The Quality team at Super covers multiple verticals and ensures high product quality in a fast-paced environment that ships new changes to production over 1000 times per month. Super.com moves fast and relies on QA to facilitate that speed. The team so far includes QA Analysts and QA Engineers, where this role will advance the team towards SDET-oriented ways of working. We leverage automation heavily for automated regression testing, drive strategy through metrics, and adopt new technologies eagerly - notably new AI tools. This team exists within the broader Infrastructure organization, so you'll work closely with TAM/PSE, DevOps, Security, and Operations Tooling engineers.
What you’ll be working on:
Define and drive the AI Enablement strategy for QA, taking the initiative, owning projects that scale, and introducing new capabilities to both QA and Engineering
Architect, build, and improve existing quality automation frameworks such as our current Playwright stack. Identify opportunities and roadmap the future of our automation.
Own the automated collection of QA metrics and operationalize the data to drive business outcomes. Identify and attribute trends in quality data and socialize learnings.
Lean in directly with our most critical projects to provide urgent, net-new, or enhanced automated coverage, particularly in domains that currently have gaps today
Contribute to coding standards and software engineering best practices, improving the quality of code written by both people and AI agents at scale
Facilitate the expansion of the QA team's capabilities into new domains, such as data, performance, and stability.
Own and improve the quality-related components of our release process, taking direct responsibility for the QA CI Strategy. Specifically, contribute to improved Cycle Time and Deployment rate without compromising quality metrics.
Mentor our QAs towards increasingly AI-enabled and automation-first ways of working
Our Technology:
Our product platform is built on a modern microservices architecture using Node.js and Python services with a React frontend.
Our test framework is written in Playwright, canary verification is through Argo, and performance monitoring is through Datadog.
We use Postgres for primary storage, Redis for caching, and Snowflake for our data warehouse.
Our infrastructure runs on AWS, leveraging technologies such as Kubernetes and RDS, with GitLab supporting version control and CI/CD.
We invest heavily in reliability and observability using Datadog for monitoring and automated alerting, and use Amplitude for client-side analytics and experimentation.
Our frontend stack includes Material-UI alongside an internal component library, with Figma supporting design collaboration.
Our platform integrates with a variety of third-party services to support compliance, risk management, and security requirements.
As an AI-First engineering organization, we also leverage modern AI development workflows using tools such as Cursor, Claude, and internally built AI agents to accelerate implementation and iteration across our codebases.
What we’re looking for:
10+ years of experience across SWE, QA, SDET, or adjacent fields, at least 3 years at a senior+ level as a SWE or SDET
AI-first thought & technical leadership: Prepared to lead and drive AI Transformation outcomes for QA
Deep test automation expertise: Thinks about quality as a platform problem
Strong full-stack coding, database, and infrastructure fundamentals: Delivers solutions independently across the entire stack from the ground up
Strongly opinionated on automated measurements of Quality metrics: Which matter, what they mean, how they're collected
Work with extreme initiative & autonomy: Identifying, delivering, measuring, and communicating staff-level initiatives
Staff-level communication and cross-functional influence