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Description
In this role, you'll design and build intelligent, automated systems that validate infrastructure changes, detect anomalies, and continuously improve the quality of AI features used by customer teams. You'll also help establish the foundational layer of a growing suite of internal applications aimed at reducing critical outages and accelerating engineering workflows. Day to day, you'll collaborate closely with cross-functional partners, translating real operational pain points into elegant, scalable automation solutions.
Minimum Qualifications
6+ years of experience in software development or QA, spanning full-stack, frontend, backend, or integrated QA roles 2+ years of hands-on experience leveraging AI tools in daily engineering workflows to automate tasks and build automated systems Proficiency in one or more scripting languages used for system automation or web development, such as Python, Ruby, or Swift Demonstrated ability to work effectively with observability and logging tooling in Kubernetes-based environments Strong cross-team communication skills with a track record of collaborating effectively with partner engineering organizations Bachelor's degree in Computer Science, Software Engineering, or a related technical field, or we may consider an equivalent practical experience
Preferred Qualifications
Swift application development experience, with familiarity building native or server-side Swift tools Proven experience meeting with stakeholders to distill ambiguous requests into well-defined workflows, engineering requirements, and measurable outcomes Familiarity with CI/CD pipeline architecture and integrating quality gates into automated delivery workflows Experience building internal developer tooling or platform engineering systems used at organizational scale
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