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Software Development Engineer in Test

Scigon SolutionsChicago, IL🇺🇸United StatesPosted 1 Sept 2026

Quick Overview

Salary
$71.3k - $95k/yr
Seniority
Mid Senior
Work mode
Hybrid
Location
Chicago, IL, United States
Posted
22 hours ago
DockerNode.jsMochaGitGitHub ActionsGitLab CIGraphQLJenkinsJiraPlaywrightTypeScriptAndroid

Job Description


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Software Development Engineer in Test

Salary: $71,250-$95,000


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Skills

  • Solid proficiency in Node.js and TypeScript; experience with test runners such as Mocha.
  • Hands-on experience with UI test automation frameworks, including Playwright.
  • Experience testing MQTT or similar Pub/Sub interfaces (e.g., WebSockets, SSE).
  • Experience testing GraphQL APIs, including writing and maintaining tests for complex queries.
  • Working knowledge of cloud environments and containerized deployments, including Docker images and container registries.
  • Working knowledge of Git and Git-based workflows, including CI/CD pipelines (e.g., GitHub Actions, GitLab CI, Jenkins).
  • Experience analyzing and correlating application and service logs across multiple services (e.g., tracing errors, debugging test failures).
  • Experience using Jira (or similar tools) for task and issue tracking.
  • Familiarity with Android test automation using frameworks such as Appium.

Responsibilities

  • Design, develop, and maintain automated tests for distributed applications, services, and platform components.
  • Lead efforts in drafting test scenarios and developing automated test coverage for new features and functional use cases.
  • Collaborate with cross-functional engineering, product, and quality teams to triage defects and investigate failures across multiple environments.
  • Monitor and maintain automated test pipelines, leveraging observability tools, test results, and application logs to identify and resolve issues.
  • Clearly document and communicate defects while proactively driving discussions that facilitate issue identification, troubleshooting, and resolution.
  • Analyze service interactions, system behavior, and application performance to improve product quality and reliability.
  • Leverage modern AI-powered tools and technologies to enhance testing efficiency, streamline development workflows, and accelerate delivery velocity.

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