Senior Software Engineer, Quality Engineering
New
J
JobgetherTravel and Rewards
Based in the United StatesFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 4+ years of full-stack software development experience building web applications and services, with 6+ years of experience expected for senior-level candidates.
- Required Skills
- AWSPythonCypressJavascriptTypeScriptC#.NETNext.jsReactPlaywright
Requirements
- 4+ years of full-stack software development experience building web applications and services, with 6+ years of experience expected for senior-level candidates.
- Demonstrated depth in software quality engineering, including test strategy, automation frameworks, regression testing, and CI-gated quality controls.
- Experience treating quality as an engineering discipline, with hands-on ownership of test infrastructure, tooling, and automated validation rather than relying solely on manual processes.
- Professional experience using AI coding agents such as Claude Code, Cursor, or GitHub Copilot, together with sound judgment about their capabilities, limitations, and failure modes.
- Strong proficiency in one or more of TypeScript/JavaScript, Python, or C#/.NET.
- Experience using modern frontend frameworks such as React, Next.js, Vue, or Angular.
- Hands-on experience with automated unit, integration, and end-to-end testing using tools such as Playwright, Cypress, Jest, Vitest, pytest, or comparable frameworks.
- Experience designing RESTful APIs, working with microservices, and delivering cloud-native applications on AWS, Azure, or GCP.
- Working knowledge of containerization and modern CI/CD practices, including Docker, Kubernetes, GitHub Actions, or equivalent technologies.
- Strong analytical and problem-solving abilities, with the judgment to identify subtle defects, evaluate AI-generated output, and distinguish genuine quality improvements from misleading signals.
- Ability to operate as a builder and independent contributor, taking ownership of complex engineering problems and translating them into scalable technical solutions.
- Familiarity with the Model Context Protocol, prompt engineering for software development, or AI evaluation frameworks is a plus.
Responsibilities
- Own and continuously raise the quality standard for AI-generated and human-written production code, evaluating software for correctness, security, performance, maintainability, and reliability.
- Design and build automated testing, regression, and AI evaluation infrastructure, including frameworks capable of detecting silent failures that traditional test suites may overlook.
- Develop and integrate automated quality workflows for testing, code-review triage, deployment validation, and release management directly into CI/CD pipelines.
- Establish practical release criteria, coverage expectations, quality signals, and engineering guardrails that enable teams to move quickly without compromising reliability.
- Build and ship full-stack features and services from development through production, maintaining a strong hands-on presence in the codebase.
- Use AI coding agents as core engineering tools, directing multi-step development workflows through effective prompting, context management, validation, and checkpoints.
- Build observability, monitoring, alerting, and guardrail dashboards that identify failures quickly and connect technical issues to their impact on end users.
- Partner with Risk and Security teams to protect sensitive member information and ensure privacy and security requirements are embedded throughout the development lifecycle.
- Share best practices, lessons learned, and emerging approaches to AI-assisted development and quality engineering with engineers across the organization.
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