Remote - Senior Software Engineer, Quality Engineering

arrivia•Scottsdale, AZ

2d•Remote

About The Position

As a Senior Software Engineer, Quality Engineering, you are a product-minded, full-stack engineer who ships faster and smarter with AI coding agents as core development tools. You will own the harder half of that equation: knowing when the output is right. As we ship faster with agents, the engineers who can tell correct code from plausible-looking code become the ones everything else rests on. This is a builder's seat, not a ticket queue. You write production code, you build the test and evaluation infrastructure other engineers depend on, and you set the quality bar for AI-generated work. Your work reaches millions of people. We build the travel and rewards platforms behind major banks, membership organizations, and travel brands, where members book real trips with real money and points, so trust is the product. The automation, guardrails, and release criteria you build are what let the rest of engineering move quickly without breaking that trust.

Requirements

4+ years of full-stack development experience building web applications and services, or 6+ years for the senior level.
Real depth in software quality: test strategy, automation frameworks, and CI-gated quality checks. You have owned quality as an engineering problem, not a process one, and you write the tests and the tooling yourself.
Hands-on use of AI coding agents such as Claude Code, Cursor, or GitHub Copilot in professional workflows, with real judgment about where they fail.
Strong proficiency in one or more of TypeScript/JavaScript, Python, or C#/.NET, plus a modern frontend framework such as React, Next.js, Vue, or Angular.
Experience with automated testing across the stack, including unit, integration, and end-to-end frameworks such as Playwright, Cypress, Jest, Vitest, or pytest.
Experience with RESTful API design, microservices, and cloud-native delivery on AWS, Azure, or GCP.
Working knowledge of containerization and CI/CD pipelines (Docker, Kubernetes, GitHub Actions or equivalent).

Nice To Haves

Familiarity with the Model Context Protocol, prompt engineering for code, or AI evaluation frameworks is a plus.
A formal CS degree is a plus, not a requirement. Depth of engineering knowledge matters most.

Responsibilities

Own the quality bar for agent output: Review and validate AI-generated code for correctness, security, performance, and maintainability, and build the tooling that makes that judgment repeatable rather than heroic.
Build test and evaluation infrastructure: Design the automated testing, regression, and AI evaluation systems other teams build on, including the harnesses that catch silent failures a green test suite would miss.
Automate the quality path: Define workflows that automate testing, code-review triage, and deployment checks, and get them into CI so they gate real releases.
Define what "ready to ship" means: Set release criteria, coverage expectations, and quality signals that teams actually use, and make the fast path the safe one.
Ship features end to end: Build and deliver full-stack features and services for our travel platform, from implementation through production. You stay in the codebase, not adjacent to it.
Work with agents as core tools: Direct AI coding agents through multi-step work using tools like Claude Code, Cursor, and GitHub Copilot, with prompts, context, and checkpoints that produce code worth shipping.
Instrument for failure: Build the observability, alerting, and guardrail dashboards that tell us what broke, how we would know, and what it means for the member.
Protect member trust: Safeguard the privacy and security of members' sensitive data alongside our Risk and Security teams.
Raise the bar around you: Share what you learn about AI-assisted development and quality practice with engineers across the team.